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The following description of the Joys of the Programming Craft was taken (and emphasis added) from Chapter 1 of the famous book The Mythical Man-Month, by Frederick P. Brooks.
Why is programming fun? What delights may its practitioner expect as his reward?
First is the sheer joy of making things. As the child delights in his mud pie, so the adult enjoys building things, especially things of his own design. I think this delight must be an image of God's delight in making things, a delight shown in the distinctness and newness of each leaf and each snowflake.
Second is the pleasure of making things that are useful to other people. Deep within, you want others to use your work and to find it helpful. In this respect the programming system is not essentially different from the child's first clay pencil holder "for Daddy's office."
Third is the fascination of fashioning complex puzzle-like objects of interlocking moving parts and watching them work in subtle cycles, playing out the consequences of principles built in from the beginning. The programmed computer has all the fascination of the pinball machine or the jukebox mechanism, carried to the ultimate.
Fourth is the joy of always learning, which springs from the nonrepeating nature of the task. In one way or another the problem is ever new, and its solver learns something: sometimes practical, sometimes theoretical, and sometimes both.
Finally, there is the delight of working in such a tractable medium. The programmer, like the poet, works only slightly removed from pure thought-stuff. He builds his castles in the air, from air, creating by the exertion of the imagination. Few media of creation are so flexible, so easy to polish and rework, so readily capable of realizing grand conceptual structures....
Yet the program construct, unlike the poet's words, is real in the sense that it moves and works, producing visible outputs separate from the construct itself. It prints results, draws pictures, produces sounds, moves arms. The magic of myth and legend has come true in our time. One types the correct incantation on a keyboard, and a display screen comes to life, showing things that never were nor could be.
Programming then is fun because it gratifies creative longings built deep within us and delights sensibilities you have in common with all men.
Not all is delight, however, and knowing the inherent woes makes it easier to bear them when they appear.
First, one must perform perfectly. The computer resembles the magic of legend in this respect, too. If one character, one pause, of the incantation is not strictly in proper form, the magic doesn't work. Human beings are not accustomed to being perfect, and few areas of human activity demand it. Adjusting to the requirement for perfection is, I think, the most difficult part of learning to program.
Next, other people set one's objectives, provide one's resources, and furnish one's information. One rarely controls the circumstances of his work, or even its goal. In management terms, one's authority is not sufficient for his responsibility. It seems that in all fields, however, the jobs where things get done never have formal authority commensurate with responsibility. In practice, actual (as opposed to formal) authority is acquired from the very momentum of accomplishment.
The dependence upon others has a particular case that is especially painful for the system programmer. He depends upon other people's programs. These are often maldesigned, poorly implemented, incompletely delivered (no source code or test cases), and poorly documented. So he must spend hours studying and fixing things that in an ideal world would be complete, available, and usable.
The next woe is that designing grand concepts is fun; finding nitty little bugs is just work. With any creative activity come dreary hours of tedious, painstaking labor, and programming is no exception.
Next, one finds that debugging has a linear convergence, or worse, where one somehow expects a quadratic sort of approach to the end. So testing drags on and on, the last difficult bugs taking more time to find than the first.
The last woe, and sometimes the last straw, is that the product over which one has labored so long appears to be obsolete upon (or before) completion. Already colleagues and competitors are in hot pursuit of new and better ideas. Already the displacement of one's thought-child is not only conceived, but scheduled.
This always seems worse than it really is. The new and better product is generally not available when one completes his own; it is only talked about. It, too, will require months of development. The real tiger is never a match for the paper one, unless actual use is wanted. Then the virtues of reality have a satisfaction all their own.
Of course the technological base on which one builds is always advancing. As soon as one freezes a design, it becomes obsolete in terms of its concepts. But implementation of real products demands phasing and quantizing. The obsolescence of an implementation must be measured against other existing implementations, not against unrealized concepts. The challenge and the mission are to find real solutions to real problems on actual schedules with available resources.
This then is programming, both a tar pit in which many efforts have floundered and a creative activity with joys and woes all its own. For many, the joys far outweigh the woes....
Object-Oriented Programming (OOP) is a programming paradigm. A programming paradigm guides programmers to analyze programming problems, and structure programming solutions, in a specific way.
Programming languages have traditionally divided the world into two parts—data and operations on data. Data is static and immutable, except as the operations may change it. The procedures and functions that operate on data have no lasting state of their own; they’re useful only in their ability to affect data.
This division is, of course, grounded in the way computers work, so it’s not one that you can easily ignore or push aside. Like the equally pervasive distinctions between matter and energy and between nouns and verbs, it forms the background against which you work. At some point, all programmers—even object-oriented programmers—must lay out the data structures that their programs will use and define the functions that will act on the data.
With a procedural programming language like C, that’s about all there is to it. The language may offer various kinds of support for organizing data and functions, but it won’t divide the world any differently. Functions and data structures are the basic elements of design.
Object-oriented programming doesn’t so much dispute this view of the world as restructure it at a higher level. It groups operations and data into modular units called objects and lets you combine objects into structured networks to form a complete program. In an object-oriented programming language, objects and object interactions are the basic elements of design.
Some other examples of programming paradigms are:
Paradigm | Programming Languages |
---|---|
Procedural Programming paradigm | C |
Functional Programming paradigm | F#, Haskell, Scala |
Logic Programming paradigm | Prolog |
Some programming languages support multiple paradigms.
Java is primarily an OOP language but it supports limited forms of functional programming and it can be used to (although not recommended to) write procedural code. e.g., se-edu/addressbook-level1
JavaScript and Python support functional, procedural, and OOP programming.
An object in Object-Oriented Programming (OOP) has state and behavior, similar to objects in the real world.
Every object has both state (data) and behavior (operations on data). In that, they’re not much different from ordinary physical objects. It’s easy to see how a mechanical device, such as a pocket watch or a piano, embodies both state and behavior. But almost anything that’s designed to do a job does, too. Even simple things with no moving parts such as an ordinary bottle combine state (how full the bottle is, whether or not it’s open, how warm its contents are) with behavior (the ability to dispense its contents at various flow rates, to be opened or closed, to withstand high or low temperatures).
It’s this resemblance to real things that gives objects much of their power and appeal. They can not only model components of real systems, but equally as well fulfill assigned roles as components in software systems.
OOP views the world as a network of interacting objects.
A real world scenario viewed as a network of interacting objects:
You are asked to find out the average age of a group of people Adam, Beth, Charlie, and Daisy. You take a piece of paper and pen, go to each person, ask for their age, and note it down. After collecting the age of all four, you enter it into a calculator to find the total. And then, use the same calculator to divide the total by four, to get the average age. This can be viewed as the objects You
, Pen
, Paper
, Calculator
, Adam
, Beth
, Charlie
, and Daisy
interacting to accomplish the end result of calculating the average age of the four persons. These objects can be considered as connected in a certain network of certain structure that dictates how these objects can interact. For example, You
object is connected to the Pen
object, and hence You
can use the Pen
object to write.
OOP solutions try to create a similar object network inside the computer’s memory – a sort of virtual simulation of the corresponding real world scenario – so that a similar result can be achieved programmatically.
OOP does not demand that the virtual world object network follow the real world exactly.
Our previous example can be tweaked a bit as follows:
Main
to represent your role in the scenario.Pen
and Paper
with an object called AgeList
that is able to keep a list of ages.Every object has both state (data) and behavior (operations on data).
The state and behavior of our running example are as follows:
Object | Real World? | Virtual World? | Example of State (i.e., Data) | Examples of Behavior (i.e., Operations) |
---|---|---|---|---|
Adam | Name, Date of Birth | Calculate age based on birthday | ||
Pen | - | Ink color, Amount of ink remaining | Write | |
AgeList | - | Recorded ages | Give the number of entries, Accept an entry to record | |
Calculator | Numbers already entered | Calculate the sum, divide | ||
You/Main | Average age, Sum of ages | Use other objects to calculate |
Every object has an interface and an implementation.
Every real world object has,
The interface and implementation of some real-world objects in our example:
Similarly, every object in the virtual world has an interface and an implementation.
The interface and implementation of some virtual-world objects in our example:
Adam
: the interface might have a method getAge(Date asAt)
; the implementation of that method is not visible to other objects.Objects interact by sending messages. Both real world and virtual world object interactions can be viewed as objects sending messages to each other. The message can result in the sender object receiving a response and/or the receiver object’s state being changed. Furthermore, the result can vary based on which object received the message, even if the message is identical (see rows 1 and 2 in the example below).
Same messages and responses from our running example:
World | Sender | Receiver | Message | Response | State Change |
---|---|---|---|---|---|
Real | You | Adam | "What is your name?" | "Adam" | - |
Real | as above | Beth | as above | "Beth" | - |
Real | You | Pen | Put nib on paper and apply pressure | Makes a mark on your paper | Ink level goes down |
Virtual | Main | Calculator (current total is 50) | add(int i): int i = 23 | 73 | total = total + 23 |
The concept of Objects in OOP is an abstraction mechanism because it allows us to abstract away the lower level details and work with bigger granularity entities i.e., ignore details of data formats and the method implementation details and work at the level of objects.
You can deal with a Person
object that represents the person Adam and query the object for Adam's age instead of dealing with details such as Adam’s date of birth (DoB), in what format the DoB is stored, the algorithm used to calculate the age from the DoB, etc.
Encapsulation protects an implementation from unintended actions and from inadvertent access.
-- Object-Oriented Programming with Objective-C, Apple
An object is an encapsulation of some data and related behavior in terms of two aspects:
1. The packaging aspect: An object packages data and related behavior together into one self-contained unit.
2. The information hiding aspect: The data in an object is hidden from the outside world and are only accessible using the object's interface.
Writing an OOP program is essentially writing instructions that the computer will use to,
A class contains instructions for creating a specific kind of objects. It turns out sometimes multiple objects keep the same type of data and have the same behavior because they are of the same kind. Instructions for creating a 'kind' (or ‘class’) of objects can be done once and those same instructions can be used to objects of that kind. We call such instructions a Class.
Classes and objects in an example scenario
Consider the example of writing an OOP program to calculate the average age of Adam, Beth, Charlie, and Daisy.
Instructions for creating objects Adam
, Beth
, Charlie
, and Daisy
will be very similar because they are all of the same kind: they all represent ‘persons’ with the same interface, the same kind of data (i.e., name
, dateOfBirth
, etc.), and the same kind of behavior (i.e., getAge(Date)
, getName()
, etc.). Therefore, you can have a class called Person
containing instructions on how to create Person
objects and use that class to instantiate objects Adam
, Beth
, Charlie
, and Daisy
.
Similarly, you need classes AgeList
, Calculator
, and Main
classes to instantiate one each of AgeList
, Calculator
, and Main
objects.
Class | Objects |
---|---|
Person | objects representing Adam, Beth, Charlie, Daisy |
AgeList | an object to represent the age list |
Calculator | an object to do the calculations |
Main | an object to represent you (i.e., the one who manages the whole operation) |
While all objects of a class have the same attributes, each object has its own copy of the attribute value.
All Person
objects have the name
attribute but the value of that attribute varies between Person
objects.
However, some attributes are not suitable to be maintained by individual objects. Instead, they should be maintained centrally, shared by all objects of the class. They are like ‘global variables’ but attached to a specific class. Such variables whose value is shared by all instances of a class are called class-level attributes.
The attribute totalPersons
should be maintained centrally and shared by all Person
objects rather than copied at each Person
object.
Similarly, when a normal method is being called, a message is being sent to the receiving object and the result may depend on the receiving object.
Sending the getName()
message to the Adam
object results in the response "Adam"
while sending the same message to the Beth
object results in the response "Beth"
.
However, there can be methods related to a specific class but not suitable for sending messages to a specific object of that class. Such methods that are called using the class instead of a specific instance are called class-level methods.
The method getTotalPersons()
is not suitable to send to a specific Person
object because a specific object of the Person
class should not have to know about the total number of Person
objects.
Class-level attributes and methods are collectively called class-level members (also called static members sometimes because some programming languages use the keyword static
to identify class-level members). They are to be accessed using the class name rather than an instance of the class.
An Enumeration is a fixed set of values that can be considered as a data type. An enumeration is often useful when using a regular data type such as int
or String
would allow invalid values to be assigned to a variable.
Suppose you want a variable called priority
to store the priority of something. There are only three priority levels: high, medium, and low. You can declare the variable priority
as of type int
and use only values 2
, 1
, and 0
to indicate the three priority levels. However, this opens the possibility of an invalid value such as 9
being assigned to it. But if you define an enumeration type called Priority
that has three values HIGH
, MEDIUM
and LOW
only, a variable of type Priority
will never be assigned an invalid value because the compiler is able to catch such an error.
Priority
: HIGH
, MEDIUM
, LOW
Objects in an OO solution need to be connected to each other to form a network so that they can interact with each other. Such connections between objects are called associations.
Suppose an OOP program for managing a learning management system creates an object structure to represent the related objects. In that object structure you can expect to have associations between a Course
object that represents a specific course and Student
objects that represent students taking that course.
Associations in an object structure can change over time.
To continue the previous example, the associations between a Course
object and Student
objects can change as students enroll in the course or drop the course over time.
Associations among objects can be generalized as associations between the corresponding classes too.
In our example, as some Course
objects can have associations with some Student
objects, you can view it as an association between the Course
class and the Student
class.
You use instance level variables to implement associations.
In our example, the Course
class can have a students
variable to keeps track of students associated with a particular course.
When two classes are linked by an association, it does not necessarily mean both objects taking part in an instance of the association knows about (i.e., has a reference to) each other. The concept of navigability tells us if an object taking part in association knows about the other. In other words, it tells us if we can 'navigate' from the one object to the other in a given direction -- because if the object 'knows' about the other, it has a reference to the other object, and we can use that reference to 'navigate to' (i.e., access) that other object.
Navigability can be unidirectional or bidirectional. Suppose there is an association between the classes Box
and Rope
, and the Box
object b
and the Rope
object r
is taking part in one instance of that association.
Box
to Rope
, b
will have a reference to r
but r
will not have a reference to b
. That is, one can navigate from b
to r
using the b
's object reference of r
(but not in the other direction).r
will have a reference to b
but b
will not have a reference to r
.b
will have a reference to r
and r
will have a reference to b
i.e., the two objects will be pointing to each other for the same single instance of the association.Note that two unidirectional associations in opposite directions do not add up to a single bidirectional association.
In the code below, there is a bidirectional association between the Person
class and the Cat
class i.e., if Person
p
is the owner of the Cat
c
, p
it will result in p
and c
having references to each other.
class Person {
Cat pet;
//...
}
class Cat{
Person owner;
//...
}
class Person:
def __init__(self):
self.pet = None # a Cat object
class Cat:
def __init__(self):
self.owner = None # a Person object
The code below has two unidirectional associations between the Person
class and the Cat
class (in opposite directions). Because the breeder is not necessarily the same person keeping the cat as a pet, they are two separate associations, not a bidirectional association.
class Person {
Cat pet;
//...
}
class Cat{
Person breeder;
//...
}
class Person:
def __init__(self):
self.pet = None # a Cat object
class Cat:
def __init__(self):
self.breeder = None # a Person object
Multiplicity is the aspect of an OOP solution that dictates how many objects take part in each association.
The multiplicity of the association between Course
objects and Student
objects tells you how many Course
objects can be associated with one Student
object and vice versa.
A normal instance-level variable gives us a 0..1
multiplicity (also called optional associations) because a variable can hold a reference to a single object or null
.
In the code below, the Logic
class has a variable that can hold 0..1
i.e., zero or one Minefield
objects.
class Logic {
Minefield minefield;
// ...
}
class Minefield {
//...
}
class Logic:
def __init__(self):
self.minefield = None
# ...
class Minefield:
# ...
A variable can be used to implement a 1
multiplicity too (also called compulsory associations).
In the code below, the Logic
class will always have a ConfigGenerator
object, provided the variable is not set to null
at some point.
class Logic {
ConfigGenerator cg = new ConfigGenerator();
...
}
In the Logic
class, ensure there is a variable that refers to a ConfigGenerator
object.
To implement other multiplicities, choose a suitable data structure such as Arrays, ArrayLists, HashMaps, Sets, etc.
This code uses a two-dimensional array to implement a 1-to-many association from the Minefield
to Cell
.
class Minefield {
Cell[][] cell;
//...
}
class Minefield:
def __init__(self):
self.cells = {1:[], 2:[], 3:[]}
In the context of OOP associations, a dependency is a need for one class to depend on another without having a direct association in the same direction. Reason for the exclusion: If there is an association from class Foo
to class Bar
(i.e., navigable from Foo
to Bar
), that means Foo
is obviously dependent on Bar
and hence there is no point in mentioning dependency specifically. In other words, we are specifically focusing on non-obvious dependencies here. One cause of such dependencies is interactions between objects that do not have a long-term link between them.
A Course
class can have a dependency on a Registrar
class because the Course
class needs to refer to the Registrar
class to obtain the maximum number of students it can support (e.g., Registrar.MAX_COURSE_CAPACITY
).
In the code below, Foo
has a dependency on Bar
but it is not an association because it is only a interaction and there is no long term relationship between a Foo
object and a Bar
object. i.e., the Foo
object does not keep the Bar
object it receives as a parameter.
class Foo {
int calculate(Bar bar) {
return bar.getValue();
}
}
class Bar {
int value;
int getValue() {
return value;
}
}
class Foo:
def calculate(self, bar):
return bar.value;
class Bar:
def __init__(self, value):
self.value = value
A composition is an association that represents a strong whole-part relationship.
A Board
(used for playing board games) consists of Square
objects.
Composition implies,
The ‘sub-folder’ association between Folder
objects is a composition type association. Consider the case of Folder
object subF
is a sub-folder of Folder
object F
. In this case,
F
is deleted, subF
will be deleted with it.F
cannot be a sub-folder of subF
(i.e., no cyclical 'sub-folder' association between the two objects).Whether a relationship is a composition can depend on the context.
Is the relationship between Email
and EmailSubject
composition? That is, is the email subject part of an email to the extent that an email subject cannot exist without an email?
A common use of composition is when parts of a big class are carved out as smaller classes for the ease of managing the internal design. In such cases, the classes extracted out still act as parts of the bigger class and the outside world has no business knowing about them.
Cascading deletion alone is not sufficient for composition. Suppose there is a design in which Person
objects are attached to Task
objects and the former get deleted whenever the latter is deleted. This fact alone does not mean there is a composition relationship between the two classes. For it to be composition, a Person
must be an integral part of a Task
in the context of that association, at the concept level (not simply at implementation level).
Identifying and keeping track of composition relationships in the design has benefits such as helping to maintain the data integrity of the system. For example, when you know that a certain relationship is a composition, you can take extra care in your implementation to ensure that when the whole object is deleted, all its parts are deleted too.
Composition is implemented using a normal variable. If correctly implemented, the ‘part’ object will be deleted when the ‘whole’ object is deleted. Ideally, the ‘part’ object may not even be visible to clients of the ‘whole’ object.
Here is one way to implement the composition between Email
and Subject
:
class Email {
private Subject subject;
...
}
class Email:
def __init__(self):
self.__subject = Subject()
In this code, the Email
has a composition type relationship with the Subject
class, in the sense that the subject is part of the email.
Aggregation represents a container-contained relationship. It is a weaker relationship than composition.
SportsClub
can act as a container for Person
objects who are members of the club. Person
objects can survive without a SportsClub
object.
Implementation is similar to that of composition except the containee object can exist even after the container object is deleted.
In the code below, there is an aggregation association between the Team
class and the Person
class in that a Team
contains a Person
object who is the leader of the team.
class Team {
Person leader;
...
void setLeader(Person p) {
leader = p;
}
}
class Team:
def __init__(self):
self.__leader = None
def set_leader(self, person):
self.__leader = person
An association class represents additional information about an association. It is a normal class but plays a special role from a design point of view.
A Man
class and a Woman
class are linked with a ‘married to’ association and there is a need to store the date of marriage. However, that data is related to the association rather than specifically owned by either the Man
object or the Woman
object. In such situations, an additional association class can be introduced, e.g., a Marriage
class, to store such information.
There is no special way to implement an association class. It can be implemented as a normal class that has variables to represent the endpoint of the association it represents.
In the code below, the Transaction
class is an association class that represents a transaction between a Person
who is the seller and another Person
who is the buyer.
class Transaction {
//all fields are compulsory
Person seller;
Person buyer;
Date date;
String receiptNumber;
Transaction(Person seller, Person buyer, Date date, String receiptNumber) {
//set fields
}
}
The OOP concept Inheritance allows you to define a new class based on an existing class.
For example, you can use inheritance to define an EvaluationReport
class based on an existing Report
class so that the EvaluationReport
class does not have to duplicate data/behaviors that are already implemented in the Report
class. The EvaluationReport
can inherit the wordCount
attribute and the print()
method from the base class Report
.
A superclass is said to be more general than the subclass. Conversely, a subclass is said to be more specialized than the superclass.
Applying inheritance on a group of similar classes can result in the common parts among classes being extracted into more general classes.
Man
and Woman
behave the same way for certain things. However, the two classes cannot be simply replaced with a more general class Person
because of the need to distinguish between Man
and Woman
for certain other things. A solution is to add the Person
class as a superclass (to contain the code common to men and women) and let Man
and Woman
inherit from Person
class.
Inheritance implies the derived class can be considered as a subtype of the base class (and the base class is a super-type of the derived class), resulting in an is a relationship.
Inheritance does not necessarily mean a subtype relationship exists. However, the two often go hand-in-hand. For simplicity, at this point let us assume inheritance implies a subtype relationship.
To continue the previous example,
Woman
is a Person
Man
is a Person
Inheritance relationships through a chain of classes can result in inheritance hierarchies (aka inheritance trees).
Two inheritance hierarchies/trees are given below. Note that the triangle points to the parent class. Observe how the Parrot
is a Bird
as well as it is an Animal
.
Multiple Inheritance is when a class inherits directly from multiple classes. Multiple inheritance among classes is allowed in some languages (e.g., Python, C++) but not in other languages (e.g., Java, C#).
The Honey
class inherits from the Food
class and the Medicine
class because honey can be consumed as a food as well as a medicine (in some oriental medicine practices). Similarly, a Car
is a Vehicle
, an Asset
and a Liability
.
Method overriding is when a subclass changes the behavior inherited from the parent class by re-implementing the method. Overridden methods have the same name, the same type signature, and the same (or a subtype of the) return type.
Consider the following case of EvaluationReport
class inheriting the Report
class:
Report methods | EvaluationReport methods | Overrides? |
---|---|---|
print() | print() | Yes |
write(String) | write(String) | Yes |
read():String | read(int):String | No. Reason: the two methods have different signatures; This is a case of overloading (rather than overriding). |
Method overloading is when there are multiple methods with the same name but different type signatures. Overloading is used to indicate that multiple operations do similar things but take different parameters.
Type signature: The type signature of an operation is the type sequence of the parameters. The return type and parameter names are not part of the type signature. However, the parameter order is significant.
Example:
Method | Type Signature |
---|---|
int add(int X, int Y) | (int, int) |
void add(int A, int B) | (int, int) |
void m(int X, double Y) | (int, double) |
void m(double X, int Y) | (double, int) |
In the case below, the calculate
method is overloaded because the two methods have the same name but different type signatures (String)
and (int)
.
calculate(String): void
calculate(int): void
An interface is a behavior specification i.e., a collection of . If a class , it means the class is able to support the behaviors specified by the said interface.
There are a number of situations in software engineering when it is important for disparate groups of programmers to agree to a "contract" that spells out how their software interacts. Each group should be able to write their code without any knowledge of how the other group's code is written. Generally speaking, interfaces are such contracts. --Oracle Docs on Java
Suppose SalariedStaff
is an interface that contains two methods setSalary(int)
and getSalary()
. AcademicStaff
can declare itself as implementing the SalariedStaff
interface, which means the AcademicStaff
class must implement all the methods specified by the SalariedStaff
interface i.e., setSalary(int)
and getSalary()
.
A class implementing an interface results in an is-a relationship, just like in class inheritance.
In the example above, AcademicStaff
is a SalariedStaff
. An AcademicStaff
object can be used anywhere a SalariedStaff
object is expected e.g., SalariedStaff ss = new AcademicStaff()
.
Abstract class: A class declared as an abstract class cannot be instantiated, but it can be subclassed.
You can declare a class as abstract when a class is merely a representation of commonalities among its subclasses in which case it does not make sense to instantiate objects of that class.
The Animal
class that exists as a generalization of its subclasses Cat
, Dog
, Horse
, Tiger
etc. can be declared as abstract because it does not make sense to instantiate an Animal
object.
Abstract method: An abstract method is a method signature without a method implementation.
The move
method of the Animal
class is likely to be an abstract method as it is not possible to implement a move
method at the Animal
class level to fit all subclasses because each animal type can move in a different way.
A class that has an abstract method becomes an abstract class because the class definition is incomplete (due to the missing method body) and it is not possible to create objects using an incomplete class definition.
Every instance of a subclass is an instance of the superclass, but not vice-versa. As a result, inheritance allows substitutability: the ability to substitute a child class object where a parent class object is expected.
An AcademicStaff
is an instance of a Staff
, but a Staff
is not necessarily an instance of an AcademicStaff
. i.e., wherever an object of the superclass is expected, it can be substituted by an object of any of its subclasses.
The following code is valid because an AcademicStaff
object is substitutable as a Staff
object.
Staff staff = new AcademicStaff(); // OK
But the following code is not valid because staff
is declared as a Staff
type and therefore its value may or may not be of type AcademicStaff
, which is the type expected by variable academicStaff
.
Staff staff;
...
AcademicStaff academicStaff = staff; // Not OK
Dynamic binding (): a mechanism where method calls in code are at , rather than at compile time.
Overridden methods are resolved using dynamic binding, and therefore resolves to the implementation in the actual type of the object.
Consider the code below. The declared type of s
is Staff
and it appears as if the adjustSalary(int)
operation of the Staff
class is invoked.
void adjustSalary(int byPercent) {
for (Staff s: staff) {
s.adjustSalary(byPercent);
}
}
However, at runtime s
can receive an object of any subclass of Staff
. That means the adjustSalary(int)
operation of the actual subclass object will be called. If the subclass does not override that operation, the operation defined in the superclass (in this case, Staff
class) will be called.
Static binding (aka early binding): When a method call is resolved at compile time.
In contrast, overloaded methods are resolved using static binding.
Note how the constructor is overloaded in the class below. The method call new Account()
is bound to the first constructor at compile time.
class Account {
Account() {
// Signature: ()
...
}
Account(String name, String number, double balance) {
// Signature: (String, String, double)
...
}
}
Similarly, the calculateGrade
method is overloaded in the code below and a method call calculateGrade("A1213232")
is bound to the second implementation, at compile time.
void calculateGrade(int[] averages) { ... }
void calculateGrade(String matric) { ... }
Polymorphism:
The ability of different objects to respond, each in its own way, to identical messages is called polymorphism. -- Object-Oriented Programming with Objective-C, Apple
Polymorphism allows you to write code targeting superclass objects, use that code on subclass objects, and achieve possibly different results based on the actual class of the object.
Assume classes Cat
and Dog
are both subclasses of the Animal
class. You can write code targeting Animal
objects and use that code on Cat
and Dog
objects, achieving possibly different results based on whether it is a Cat
object or a Dog
object. Some examples:
Animal
and still be able to store Dog
and Cat
objects in it.Animal
object as a parameter and yet be able to pass Dog
and Cat
objects to it.Dog
or a Cat
object as if it is an Animal
object (i.e., without knowing whether it is a Dog
object or a Cat
object) and get a different response from it based on its actual class e.g., call the Animal
class's method speak()
on object a
and get a "Meow"
as the return value if a
is a Cat
object and "Woof"
if it is a Dog
object.Polymorphism literally means "ability to take many forms".
Three concepts combine to achieve polymorphism: substitutability, operation overriding, and dynamic binding.
What is the difference between a Class, an Abstract Class, and an Interface?
How does overriding differ from overloading?
Overloading is used to indicate that multiple operations do similar things but take different parameters. Overloaded methods have the same method name but different method signatures and possibly different return types.
Overriding is when a sub-class redefines an operation using the same method name and the same type signature. Overridden methods have the same name, same method signature, and same return type.
A software requirement specifies a need to be fulfilled by the software product.
A software project may be,
In either case, requirements need to be gathered, analyzed, specified, and managed.
Requirements come from stakeholders.
Stakeholder: An individual or an organization that is involved or potentially affected by the software project. e.g., users, sponsors, developers, interest groups, government agencies, etc.
Identifying requirements is often not easy. For example, stakeholders may not be aware of their precise needs, may not know how to communicate their requirements correctly, may not be willing to spend effort in identifying requirements, etc.
Requirements can be divided into two in the following way:
Some examples of non-functional requirement categories:
You may have to spend an extra effort in digging NFRs out as early as possible because,
Here are some characteristics of well-defined requirements [📖 zielczynski]:
Besides these criteria for individual requirements, the set of requirements as a whole should be
Requirements can be prioritized based on the importance and urgency, while keeping in mind the constraints of schedule, budget, staff resources, quality goals, and other constraints.
A common approach is to group requirements into priority categories. Note that all such scales are subjective, and stakeholders define the meaning of each level in the scale for the project at hand.
An example scheme for categorizing requirements:
Essential
: The product must have this requirement fulfilled or else it does not get user acceptance.Typical
: Most similar systems have this feature although the product can survive without it.Novel
: New features that could differentiate this product from the rest.Other schemes:
High
, Medium
, Low
Must-have
, Nice-to-have
, Unlikely-to-have
Level 0
, Level 1
, Level 2
, ...Some requirements can be discarded if they are considered ‘out of ’.
The requirement given below is for a Calendar application. Stakeholders of the software (e.g. product designers) might decide the following requirement is not in the scope of the software.
The software records the actual time taken by each task and show the difference between the actual and scheduled time for the task.
Brainstorming: A group activity designed to generate a large number of diverse and creative ideas for the solution of a problem.
In a brainstorming session there are no "bad" ideas. The aim is to generate ideas; not to validate them. Brainstorming encourages you to "think outside the box" and put "crazy" ideas on the table without fear of rejection.
Surveys can be used to solicit responses and opinions from a large number of stakeholders regarding a current product or a new product.
Observing users in their natural work environment can uncover product requirements. Usage data of an existing system can also be used to gather information about how an existing system is being used, which can help in building a better replacement e.g. to find the situations where the user makes mistakes when using the current system.
Interviewing stakeholders and domain experts can produce useful information about project requirements.
[source]
Focus groups are a kind of informal interview within an interactive group setting. A group of people (e.g. potential users, beta testers) are asked about their understanding of a specific issue, process, product, advertisement, etc.
Prototype: A prototype is a mock up, a scaled down version, or a partial system constructed
Prototyping can uncover requirements, in particular, those related to how users interact with the system. UI prototypes or mock ups are often used in brainstorming sessions, or in meetings with the users to get quick feedback from them.
A mock up (also called a wireframe diagram) of a dialog box:
[source: plantuml.com]
Prototyping can be used for discovering as well as specifying requirements e.g. a UI prototype can serve as a specification of what to build.
Studying existing products can unearth shortcomings of existing solutions that can be addressed by a new product. Product manuals and other forms of documentation of an existing system can tell us how the existing solutions work.
When developing a game for a mobile device, a look at a similar PC game can give insight into the kind of features and interactions the mobile game can offer.
A textual description (i.e., prose) can be used to describe requirements. Prose is especially useful when describing abstract ideas such as the vision of a product.
The product vision of the TEAMMATES Project given below is described using prose.
TEAMMATES aims to become the biggest student project in the world (biggest here refers to 'many contributors, many users, large codebase, evolving over a long period'). Furthermore, it aims to serve as a training tool for Software Engineering students who want to learn SE skills in the context of a non-trivial real software product.
Avoid using lengthy prose to describe requirements; they can be hard to follow.
Feature list: A list of features of a product grouped according to some criteria such as aspect, priority, order of delivery, etc.
A sample feature list from a simple Minesweeper game (only a brief description has been provided to save space):
User story: User stories are short, simple descriptions of a feature told from the perspective of the person who desires the new capability, usually a user or customer of the system. [Mike Cohn]
A common format for writing user stories is:
User story format: As a {user type/role} I can {function} so that {benefit}
Examples (from a Learning Management System):
You can write user stories using a physical medium or a digital tool. For example, you can use index cards or sticky notes, and arrange them on walls or tables. Alternatively, you can use a software (e.g., GitHub Project Boards, Trello, Google Docs, ...) to manage user stories digitally.
The {benefit}
can be omitted if it is obvious.
As a user, I can login to the system so that I can access my data
It is recommended to confirm there is a concrete benefit even if you omit it from the user story. If not, you could end up adding features that have no real benefit.
You can add more characteristics to the {user role}
to provide more context to the user story.
You can write user stories at various levels. High-level user stories, called epics (or themes) cover bigger functionality. You can then break down these epics to multiple user stories of normal size.
[Epic] As a lecturer, I can monitor student participation levels
You can add conditions of satisfaction to a user story to specify things that need to be true for the user story implementation to be accepted as ‘done’.
As a lecturer, I can view the forum post count of each student so that I can identify the activity level of students in the forum.
Conditions:
Separate post count for each forum should be shown
Total post count of a student should be shown
The list should be sortable by student name and post count
Other useful info that can be added to a user story includes (but not limited to)
User stories capture user requirements in a way that is convenient for , , and .
[User stories] strongly shift the focus from writing about features to discussing them. In fact, these discussions are more important than whatever text is written. [Mike Cohn, MountainGoat Software 🔗]
User stories differ from mainly in the level of detail. User stories should only provide enough details to make a reasonably low risk estimate of how long the user story will take to implement. When the time comes to implement the user story, the developers will meet with the customer face-to-face to work out a more detailed description of the requirements. [more...]
User stories can capture non-functional requirements too because even NFRs must benefit some stakeholder.
An example of an NFR captured as a user story:
As a/an ___, | I want to ___, | so that ___. |
---|---|---|
impatient user | to be able to experience reasonable response time from the website while up to 1000 concurrent users are using it | I can use the app even when the traffic is at the maximum expected level |
Given their lightweight nature, user stories are quite handy for recording requirements during early stages of requirements gathering.
Given below is a possible recipe you can take when using user stories for early stages of requirement gathering.
Step 0: Clear your mind of preconceived product ideas
Even if you already have some idea of what your product will look/behave like in the end, clear your mind of those ideas. The product is the solution. At this point, we are still at the stage of figuring out the problem (i.e., user requirements). Let's try to get from the problem to the solution in a systematic way, one step at a time.
Step 1: Define the target user as a persona:
Decide your target user's profile (e.g. a student, office worker, programmer, salesperson) and work patterns (e.g. Does he work in groups or alone? Does he share his computer with others?). A clear understanding of the target user will help when deciding the importance of a user story. You can even narrow it down to a persona. Here is an example:
Jean is a university student studying in a non-IT field. She interacts with a lot of people due to her involvement in university clubs/societies. ...
Step 2: Define the problem scope:
Decide the exact problem you are going to solve for the target user. It is also useful to specify what related problems it will not solve so that the exact scope is clear.
ProductX helps Jean keep track of all her school contacts. It does not cover communicating with contacts.
Step 3: List scenarios to form a narrative:
Think of the various scenarios your target user is likely to go through as she uses your app. Following a chronological sequence as if you are telling a story might be helpful.
A. First use:
- Jean gets to know about ProductX. She downloads it and launches it to check out what it can do.
- After playing around with the product for a bit, Jean wants to start using it for real.
- ...
B. Second use: (Jean is still a beginner)
- Jean launches ProductX. She wants to find ...
- ...
C. 10th use: (Jean is a little bit familiar with the app)
- ...
D. 100th use: (Jean is an expert user)
- Jean launches the app and does ... and ... followed by ... as per her usual habit.
- Jean feels some of the data in the app are no longer needed. She wants to get rid of them to reduce clutter.
More examples that might apply to some products:
- Jean uses the app at the start of the day to ...
- Jean uses the app before going to sleep to ...
- Jean hasn't used the app for a while because she was on a three-month training programme. She is now back at work and wants to resume her daily use of the app.
- Jean moves to another company. Some of her clients come with her but some don't.
- Jean starts freelancing in her spare time. She wants to keep her freelancing clients separate from her other clients.
Step 4: List the user stories to support the scenarios:
Based on the scenarios, decide on the user stories you need to support. For example, based on the scenario 'A. First use', you might have user stories such as these:
- As a potential user exploring the app, I can see the app populated with sample data, so that I can easily see how the app will look like when it is in use.
- As a user ready to start using the app, I can purge all current data, so that I can get rid of sample/experimental data I used for exploring the app.
To give another example, based on the scenario 'D. 100th use', you might have user stories such as these:
- As an expert user, I can create shortcuts for tasks, so that I can save time on frequently performed tasks.
- As a long-time user, I can archive/hide unused data, so that I am not distracted by irrelevant data.
Do not 'evaluate' the value of user stories while brainstorming. Reason: an important aspect of brainstorming is not judging the ideas generated.
Other tips:
As a user, I want to see a list of tasks that need my attention most at the present time, so that I pay attention to them first.
While use cases can be recorded on in the initial stages, an online tool is more suitable for longer-term management of user stories, especially if the team is not .
Use case: A description of a set of sequences of actions, including variants, that a system performs to yield an observable result of value to an actor [ 📖 : ].
A use case describes an interaction between the user and the system for a specific functionality of the system.
UML includes a diagram type called use case diagrams that can illustrate use cases of a system visually, providing a visual ‘table of contents’ of the use cases of a system.
In the example on the right, note how use cases are shown as ovals and user roles relevant to each use case are shown as stick figures connected to the corresponding ovals.
Use cases capture the functional requirements of a system.
A use case is an interaction between a system and its actors.
Actors in Use Cases
Actor: An actor (in a use case) is a role played by a user. An actor can be a human or another system. Actors are not part of the system; they reside outside the system.
Some example actors for a Learning Management System:
A use case can involve multiple actors.
An actor can be involved in many use cases.
A single person/system can play many roles.
Many persons/systems can play a single role.
Use cases can be specified at various levels of detail.
Consider the three use cases given below. Clearly, (a) is at a higher level than (b) and (b) is at a higher level than (c).
While modeling user-system interactions,
Writing use case steps
The main body of the use case is a sequence of steps that describes the interaction between the system and the actors. Each step is given as a simple statement describing who does what.
An example of the main body of a use case.
A use case describes only the externally visible behavior, not internal details, of a system i.e., should minimize details that are not part of the interaction between the user and the system.
This example use case step refers to a behavior not externally visible (i.e., user is not meant to be aware of).
A step gives the intention of the actor (not the mechanics). That means UI details are usually omitted. The idea is to leave as much flexibility to the UI designer as possible. That is, the use case specification should be as general as possible (less specific) about the UI.
The first example below is not a good use case step because it contains UI-specific details. The second one is better because it omits UI-specific details.
Bad : User right-clicks the text box and chooses ‘clear’
Good : User clears the input
A use case description can show loops too.
An example of how you can show a loop:
Software System: SquareGame
Use case: - Play a Game
Actors: Player (multiple players)
MSS:
Use case ends.
The Main Success Scenario (MSS) describes the most straightforward interaction for a given use case, which assumes that nothing goes wrong. This is also called the Basic Course of Action or the Main Flow of Events of a use case.
Note how the MSS in the example below assumes that all entered details are correct and ignores problems such as timeouts, network outages etc. For example, the MSS does not tell us what happens if the user enters incorrect data.
System: Online Banking System (OBS)
Use case: UC23 - Transfer Money
Actor: User
MSS:
Use case ends.
Extensions are "add-on"s to the MSS that describe exceptional/alternative flow of events. They describe variations of the scenario that can happen if certain things are not as expected by the MSS. Extensions appear below the MSS.
This example adds some extensions to the use case in the previous example.
System: Online Banking System (OBS) Use case: UC23 - Transfer Money Actor: User MSS: 1. User chooses to transfer money. 2. OBS requests for details of the transfer. 3. User enters the requested details. 4. OBS requests for confirmation. 5. User confirms. 6. OBS transfers the money and displays the new account balance. Use case ends.
Extensions: 3a. OBS detects an error in the entered data. 3a1. OBS requests for the correct data. 3a2. User enters new data. Steps 3a1-3a2 are repeated until the data entered are correct. Use case resumes from step 4. 3b. User requests to effect the transfer in a future date. 3b1. OBS requests for confirmation. 3b2. User confirms future transfer. Use case ends. *a. At any time, User chooses to cancel the transfer. *a1. OBS requests to confirm the cancellation. *a2. User confirms the cancellation. Use case ends. *b. At any time, 120 seconds lapse without any input from the User. *b1. OBS cancels the transfer. *b2. OBS informs the User of the cancellation. Use case ends.
Note that the numbering style is not a universal rule but a widely used convention. Based on that convention,
3a.
and 3b.
can happen just after step 3
of the MSS.*a.
can happen at any step (hence, the *
).When separating extensions from the MSS, keep in mind that the MSS should be self-contained. That is, the MSS should give us a complete usage scenario.
Also note that it is not useful to mention events such as power failures or system crashes as extensions because the system cannot function beyond such catastrophic failures.
In use case diagrams you can use the <<extend>>
arrows to show extensions. Note the direction of the arrow is from the extension to the use case it extends and the arrow uses a dashed line.
A use case can include another use case. Underlined text is used to show an inclusion of a use case.
This use case includes two other use cases, one in step 1 and one in step 2.
Inclusions are useful,
You use a dotted arrow and an <<include>>
annotation to show use case inclusions in a use case diagram. Note how the arrow direction is different from the <<extend>>
arrows.
Preconditions specify the specific state you expect the system to be in before the use case starts.
Software System: Online Banking System
Use case: UC23 - Transfer Money
Actor: User
Preconditions: User is logged in
MSS:
Guarantees specify what the use case promises to give us at the end of its operation.
Software System: Online Banking System
Use case: UC23 - Transfer Money
Actor: User
Preconditions: User is logged in.
Guarantees:
MSS:
You can use actor generalization in use case diagrams using a symbol similar to that of UML notation for inheritance.
In this example, actor Blogger
can do all the use cases the actor Guest
can do, as a result of the actor generalization relationship given in the diagram.
Do not over-complicate use case diagrams by trying to include everything possible. A use case diagram is a brief summary of the use cases that is used as a starting point. Details of the use cases can be given in the use case descriptions.
Some include ‘System’ as an actor to indicate that something is done by the system itself without being initiated by a user or an external system.
The diagram below can be used to indicate that the system generates daily reports at midnight.
However, others argue that only use cases providing value to an external user/system should be shown in the use case diagram. For example, they argue that view daily report
should be the use case and generate daily report
is not to be shown in the use case diagram because it is simply something the system has to do to support the view daily report
use case.
You are recommended to follow the latter view (i.e., not to use System as a user). Limit use cases for modeling behaviors that involve an external actor.
UML is not very specific about the text contents of a use case. Hence, there are many styles for writing use cases. For example, the steps can be written as a continuous paragraph.
Use cases should be easy to read. Note that there is no strict rule about writing all details of all steps or a need to use all the elements of a use case.
There are some advantages of documenting system requirements as use cases:
One of the main disadvantages of use cases is that they are not good for capturing requirements that do not involve a user interacting with the system. Hence, they should not be used as the sole means to specify requirements.
Glossary: A glossary serves to ensure that all stakeholders have a common understanding of the noteworthy terms, abbreviations, acronyms etc.
Here is a partial glossary from a variant of the Snakes and Ladders game:
Design is the creative process of transforming the problem into a solution; the solution is also called design. -- 📖 Software Engineering Theory and Practice, Shari Lawrence; Atlee, Joanne M. Pfleeger
Software design has two main aspects:
Abstraction is a technique for dealing with complexity. It works by establishing a level of complexity we are interested in, and suppressing the more complex details below that level.
The guiding principle of abstraction is that only details that are relevant to the current perspective or the task at hand need to be considered. As most programs are written to solve complex problems involving large amounts of intricate details, it is impossible to deal with all these details at the same time. That is where abstraction can help.
Data abstraction: abstracting away the lower level data items and thinking in terms of bigger entities
Within a certain software component, you might deal with a user data type, while ignoring the details contained in the user data item such as name, and date of birth. These details have been ‘abstracted away’ as they do not affect the task of that software component.
Control abstraction: abstracting away details of the actual control flow to focus on tasks at a higher level
print(“Hello”)
is an abstraction of the actual output mechanism within the computer.
Abstraction can be applied repeatedly to obtain progressively higher levels of abstraction.
An example of different levels of data abstraction: a File
is a data item that is at a higher level than an array and an array is at a higher level than a bit.
An example of different levels of control abstraction: execute(Game)
is at a higher level than print(Char)
which is at a higher level than an Assembly language instruction MOV
.
Abstraction is a general concept that is not limited to just data or control abstractions.
Some more general examples of abstraction:
Coupling is a measure of the degree of dependence between components, classes, methods, etc. Low coupling indicates that a component is less dependent on other components. High coupling (aka tight coupling or strong coupling) is discouraged due to the following disadvantages:
In the example below, design A
appears to have more coupling between the components than design B
.
X is coupled to Y if a change to Y can potentially require a change in X.
If the Foo
class calls the method Bar#read()
, Foo
is coupled to Bar
because a change to Bar
can potentially (but not always) require a change in the Foo
class e.g. if the signature of Bar#read()
is changed, Foo
needs to change as well, but a change to the Bar#write()
method may not require a change in the Foo
class because Foo
does not call Bar#write()
.
Some examples of coupling: A
is coupled to B
if,
A
has access to the internal structure of B
(this results in a very high level of coupling)A
and B
depend on the same global variableA
calls B
A
receives an object of B
as a parameter or a return valueA
inherits from B
A
and B
are required to follow the same data format or communication protocolCohesion is a measure of how strongly-related and focused the various responsibilities of a component are. A highly-cohesive component keeps related functionalities together while keeping out all other unrelated things.
Higher cohesion is better. Disadvantages of low cohesion (aka weak cohesion):
Cohesion can be present in many forms. Some examples:
Student
component handles everything related to students.GameArchive
component handles everything related to the storage and retrieval of game sessions.Suppose a Payroll application contains a class that deals with writing data to the database. If the class includes some code to show an error dialog to the user if the database is unreachable, that class is not cohesive because it seems to be interacting with the user as well as the database.
A model is a representation of something else.
A class diagram is a model that represents a software design.
A model provides a simpler view of a complex entity because a model captures only a selected aspect. This omission of some aspects implies models are abstractions.
A class diagram captures the structure of the software design but not the behavior.
Multiple models of the same entity may be needed to capture it fully.
In addition to a class diagram (or even multiple class diagrams), a number of other diagrams may be needed to capture various interesting aspects of the software.
In software development, models are useful in several ways:
a) To analyze a complex entity related to software development.
Some examples of using models for analysis:
b) To communicate information among stakeholders. Models can be used as a visual aid in discussions and documentation.
Some examples of using models to communicate:
c) As a blueprint for creating software. Models can be used as instructions for building software.
Some examples of using models as blueprints:
Unified Modeling Language (UML) is a graphical notation to describe various aspects of a software system. UML is the brainchild of three software modeling specialists James Rumbaugh, Grady Booch and Ivar Jacobson (also known as the Three Amigos). Each of them had developed their own notation for modeling software systems before joining forces to create a unified modeling language (hence, the term ‘Unified’ in UML). UML is currently the most commonly used modeling notation used in the software industry.
The following diagram uses the class diagram notation to show the different types of UML diagrams.
source:https://en.wikipedia.org/
An OO solution is basically a network of objects interacting with each other. Therefore, it is useful to be able to model how the relevant objects are 'networked' together inside a software i.e., how the objects are connected together.
Given below is an illustration of some objects and how they are connected together. Note: the diagram uses an ad-hoc notation.
Note that these object structures within the same software can change over time.
Given below is how the object structure in the previous example could have looked like at a different time.
However, object structures do not change at random; they change based on a set of rules set by the designer of that software. Those rules that object structures need to follow can be illustrated as a class structure i.e., a structure that exists among the relevant classes.
Here is a class structure (drawn using an ad-hoc notation) that matches the object structures given in the previous two examples. For example, note how this class structure does not allow any connection between Genre
objects and Author
objects, a rule followed by the two object structures above.
UML Object Diagrams model object structures. UML Class Diagrams model class structures.
Here is an object diagram for the above example:
And here is the class diagram for it:
Classes form the basis of class diagrams.
Associations are the main connections among the classes in a class diagram.
The most basic class diagram is a bunch of classes with some solid lines among them to represent associations, such as this one.
An example class diagram showing associations between classes.
In addition, associations can show additional decorations such as association labels, association roles, multiplicity and navigability to add more information to a class diagram.
Here is the same class diagram shown earlier but with some additional information included:
A class diagram can also show different types of relationships between classes: inheritance, compositions, aggregations, dependencies.
A class diagram can also show different types of class-like entities:
Object diagrams can be used to complement class diagrams. For example, you can use object diagrams to model different object structures that can result from a design represented by a given class diagram.
The analysis process for identifying objects and object classes is recognized as one of the most difficult areas of object-oriented development. --Ian Sommerville, in the book Software Engineering
Sidebar: Domain Modeling
Domain modeling is modeling the i.e., to model how things actually work in the real world. Domain modeling is useful in understanding the problem domain, which is essential to the success of a project.
Domain modeling can be done using,
When building an OOP system, it makes sense to build OOP models of the problem domain, given OOP aspires to emulate the objects in the real world.
The UML model that captures class structures in the problem domain are called conceptual class diagrams. They are in fact a lighter version of class diagrams, and sometimes also called OO domain models (OODMs). The latter name is somewhat misleading as conceptual class diagrams (CCDs) are actually only one type of domain models that can model an OOP problem domain.
The CCD of a snakes and ladders game is given below.
Description: The snakes and ladders game is played by two or more players using a board and a die. The board has 100 squares marked 1 to 100. Each player owns one piece. Players take turns to throw the die and advance their piece by the number of squares they earned from the die throw. The board has a number of snakes. If a player’s piece lands on a square with a snake head, the piece is automatically moved to the square containing the snake’s tail. Similarly, a piece can automatically move from a ladder foot to the ladder top. The player whose piece is the first to reach the 100th square wins.
CCDs do not contain solution-specific classes (i.e., classes that are used in the solution domain but do not exist in the problem domain). For example, a class called DatabaseConnection could appear in a class diagram but not usually in a CCD because DatabaseConnection is something related to a software solution but not an entity in the problem domain.
CCDs represents the class structure of the problem domain and not their behavior, just like class diagrams. To show behavior, use other diagrams such as sequence diagrams.
CCD notation is a subset of the class diagram notation (omits methods and navigability).
Software projects often involve workflows. Workflows define the flow in which a process or a set of tasks is executed. Understanding such workflows is important for the success of the software project.
Some examples in which a certain workflow is relevant to software project:
A software that automates the work of an insurance company needs to take into account the workflow of processing an insurance claim.
The algorithm of a piece of code represents the workflow (i.e., the execution flow) of the code.
Sequence diagrams model the interactions between various entities in a system, in a specific scenario. Modelling such scenarios is useful, for example, to verify the design of the internal interactions is able to provide the expected outcomes.
Some examples where a sequence diagram can be used:
To model how components of a system interact with each other to respond to a user action.
To model how objects inside a component interact with each other to respond to a method call it received from another component.
You can use models to analyze and design software before you start coding.
Suppose you are planning to implement a simple minesweeper game that has a text based UI and a GUI. Given below is a possible OOP design for the game.
Before jumping into coding, you may want to find out things such as,
To answer these questions, you can analyze how the objects of these classes will interact with each other to produce the behavior you want.
As mentioned in [Design → Modeling → Modeling a Solution → Introduction], this is the Minesweeper design you have come up with so far. Our objective is to analyze, evaluate, and refine that design.
Let us start by modeling a sample interaction between the person playing the game and the TextUi
object.
newgame
and clear x y
represent commands typed by the Player
on the TextUi
.
How does the TextUi
object carry out the requests it has received from the player? It would need to interact with other objects of the system. Because the Logic
class is the one that controls the game logic, the TextUi
needs to collaborate with Logic
to fulfill the newgame
request. Let us extend the model to capture that interaction.
W
= Width of the minefield; H
= Height of the minefield
The above diagram assumes that W
and H
are the only information TextUi
requires to display the minefield to the Player
. Note that there could be other ways of doing this.
The Logic
methods you conceptualized in our modeling so far are:
Now, let us look at what other objects and interactions are needed to support the newGame()
operation. It is likely that a new Minefield
object is created when the newGame()
method is called.
Note that the behavior of the Minefield
constructor has been abstracted away. It can be designed at a later stage.
Given below are the interactions between the player and the TextUi
for the whole game.
Note that can be used when discovering/defining the architecture-level APIs.
Defining the architecture-level APIs for a small Tic-Tac-Toe game:
The software architecture of a program or computing system is the structure or structures of the system, which comprise software elements, the externally visible properties of those elements, and the relationships among them. Architecture is concerned with the public side of interfaces; private details of elements—details having to do solely with internal implementation—are not architectural. -- Software Architecture in Practice (2nd edition), Bass, Clements, and Kazman
The software architecture shows the overall organization of the system and can be viewed as a very high-level design. It usually consists of a set of interacting components that fit together to achieve the required functionality. It should be a simple and technically viable structure that is well-understood and agreed-upon by everyone in the development team, and it forms the basis for the implementation.
A possible architecture for a Minesweeper game:
![]() | ![]() |
Main components:
GUI
: Graphical user interfaceTextUi
: Textual user interfaceATD
: An automated test driver used for testing the game logicLogic
: Computation and logic of the gameStore
: Storage and retrieval of game data (high scores etc.)The architecture is typically designed by the software architect, who provides the technical vision of the system and makes high-level (i.e., architecture-level) technical decisions about the project.
Architecture diagrams are free-form diagrams. There is no universally adopted standard notation for architecture diagrams. Any symbols that reasonably describe the architecture may be used.
Some example architecture diagrams:
While architecture diagrams have no standard notation, try to follow these basic guidelines when drawing them.
Minimize the variety of symbols. If the symbols you choose do not have widely-understood meanings e.g., A drum symbol is widely-understood as representing a database, explain their meaning.
Avoid the indiscriminate use of double-headed arrows to show interactions between components.
Consider the two architecture diagrams of the same software given below. Because Diagram 2
uses double-headed arrows, the important fact that GUI has a bidirectional dependency with the Logic component is no longer captured.
Software architectures follow various high-level styles (aka architectural patterns), just like how building architectures follow various architecture styles.
n-tier style, client-server style, event-driven style, transaction processing style, service-oriented style, pipes-and-filters style, message-driven style, broker style, ...
The client-server style has at least one component playing the role of a server and at least one client component accessing the services of the server. This is an architectural style used often in distributed applications.
The online game and the web application below use the client-server style.
The transaction processing style divides the workload of the system down to a number of transactions which are then given to a dispatcher that controls the execution of each transaction. Task queuing, ordering, undo etc. are handled by the dispatcher.
In this example from a banking system, transactions are generated by the terminals used by , which are then sent to a central dispatching unit, which in turn dispatches the transactions to various other units to execute.
The service-oriented architecture (SOA) style builds applications by combining functionalities packaged as programmatically accessible services. SOA aims to achieve interoperability between distributed services, which may not even be implemented using the same programming language. A common way to implement SOA is through the use of XML web services where the web is used as the medium for the services to interact, and XML is used as the language of communication between service providers and service users.
Suppose that Amazon.com provides a web service for customers to browse and buy merchandise, while HSBC provides a web service for merchants to charge HSBC credit cards. Using these web services, an ‘eBookShop’ web application can be developed that allows HSBC customers to buy merchandise from Amazon and pay for them using HSBC credit cards. Because both Amazon and HSBC services follow the SOA architecture, their web services can be reused by the web application, even if all three systems use different programming platforms.
Event-driven style controls the flow of the application by detecting from event emitters and communicating those events to interested event consumers. This architectural style is often used in GUIs.
When the ‘button clicked’ event occurs in a GUI, that event can be transmitted to components that are interested in reacting to that event. Similarly, events detected at a printer port can be transmitted to components related to operating the printer. The same event can be sent to multiple consumers too.
Design pattern: An elegant reusable solution to a commonly recurring problem within a given context in software design.
In software development, there are certain problems that recur in a certain context.
Some examples of recurring design problems:
Design Context | Recurring Problem |
---|---|
Assembling a system that makes use of other existing systems implemented using different technologies | What is the best architecture? |
UI needs to be updated when the data in the application backend changes | How to initiate an update to the UI when data changes without coupling the backend to the UI? |
After repeated attempts at solving such problems, better solutions are discovered and refined over time. These solutions are known as design patterns, a term popularized by the seminal book Design Patterns: Elements of Reusable Object-Oriented Software by the so-called "Gang of Four" (GoF) written by Erich Gamma, Richard Helm, Ralph Johnson, and John Vlissides.
The common format to describe a pattern consists of the following components:
Context
Certain classes should have no more than just one instance (e.g. the main controller class of the system). These single instances are commonly known as singletons.
Problem
A normal class can be instantiated multiple times by invoking the constructor.
Solution
Make the constructor of the singleton class private
, because a public
constructor will allow others to instantiate the class at will. Provide a public
class-level method to access the single instance.
Example:
The <<Singleton>>
in the class above uses the UML stereotype notation, which is used to (optionally) indicate the purpose or the role played by a UML element. In this example, the class Logic
is playing the role of a Singleton class. The general format is <<role/purpose>>
.
Here is the typical implementation of how the Singleton pattern is applied to a class:
class Logic {
private static Logic theOne = null;
private Logic() {
...
}
public static Logic getInstance() {
if (theOne == null) {
theOne = new Logic();
}
return theOne;
}
}
Notes:
private
, which prevents instantiation from outside the class.private
class-level variable.public
class-level operation getInstance()
which instantiates a single copy of the singleton class when it is executed for the first time. Subsequent calls to this operation return the single instance of the class.If Logic
was not a Singleton class, a Logic
object can be created as follows:
Logic m = new Logic();
But when it is a Singleton class, the single Logic
object needs to be accessed as follows:
Logic m = Logic.getInstance();
Pros:
Cons:
Given that there are some significant cons, it is recommended that you apply the Singleton pattern when, in addition to requiring only one instance of a class, there is a risk of creating multiple objects by mistake, and creating such multiple objects has real negative consequences.
Context
Components need to access functionality deep inside other components.
The UI
component of a Library
system might want to access functionality of the Book
class contained inside the Logic
component.
Problem
Access to the component should be allowed without exposing its internal details. e.g. the UI
component should access the functionality of the Logic
component without knowing that it contains a Book
class within it.
Solution
Include a class that sits between the component internals and users of the component such that all access to the component happens through the Facade class.
The following class diagram applies the Facade pattern to the Library System
example. The LibraryLogic
class is the Facade class.
Context
A system is required to execute a number of commands, each doing a different task. For example, a system might have to support Sort
, List
, Reset
commands.
Problem
It is preferable that some part of the code executes these commands without having to know each command type. e.g., there can be a CommandQueue
object that is responsible for queuing commands and executing them without knowledge of what each command does.
Solution
The essential element of this pattern is to have a general <<Command>>
object that can be passed around, stored, executed, etc without knowing the type of command (i.e., via polymorphism).
Let us examine an example application of the pattern first:
In the example solution below, the CommandCreator
creates List
, Sort
, and Reset Command
objects and adds them to the CommandQueue
object. The CommandQueue
object treats them all as Command
objects and performs the execute/undo operation on each of them without knowledge of the specific Command
type. When executed, each Command
object will access the DataStore
object to carry out its task. The Command
class can also be an abstract class or an interface.
The general form of the solution is as follows.
The <<Client>>
creates a <<ConcreteCommand>>
object, and passes it to the <<Invoker>>
. The <<Invoker>>
object treats all commands as a general <<Command>>
type. <<Invoker>>
issues a request by calling execute()
on the command. If a command is undoable, <<ConcreteCommand>>
will store the state for undoing the command prior to invoking execute()
. In addition, the <<ConcreteCommand>>
object may have to be linked to any <<Receiver>>
of the command () before it is passed to the <<Invoker>>
. Note that an application of the command pattern does not have to follow the structure given above.
Context
Most applications support storage/retrieval of information, displaying of information to the user (often via multiple UIs having different formats), and changing stored information based on external inputs.
Problem
The high coupling that can result from the interlinked nature of the features described above.
Solution
Decouple data, presentation, and control logic of an application by separating them into three different components: Model, View and Controller.
The relationship between the components can be observed in the diagram below. Typically, the UI is the combination of View and Controller.
Given below is a concrete example of MVC applied to a student management system. In this scenario, the user is retrieving the data of a student.
In the diagram above, when the user clicks on a button using the UI, the ‘click’ event is caught and handled by the UiController
. The ref
frame indicates that the interactions within that frame have been extracted out to another separate sequence diagram.
Note that in a simple UI where there’s only one view, Controller and View can be combined as one class.
There are many variations of the MVC model used in different domains. For example, the one used in a desktop GUI could be different from the one used in a web application.
Context
An object (possibly more than one) is interested in being notified when a change happens to another object. That is, some objects want to ‘observe’ another object.
Consider this scenario from a student management system where the user is adding a new student to the system.
Now, assume the system has two additional views used in parallel by different users:
StudentListUi
: that accesses a list of students andStudentStatsUi
: that generates statistics of current students.When a student is added to the database using NewStudentUi
shown above, both StudentListUi
and StudentStatsUi
should get updated automatically, as shown below.
However, the StudentList
object has no knowledge about StudentListUi
and StudentStatsUi
(note the direction of the navigability) and has no way to inform those objects. This is an example of the type of problem addressed by the Observer pattern.
Problem
The ‘observed’ object does not want to be coupled to objects that are ‘observing’ it.
Solution
Force the communication through an interface known to both parties.
Here is the Observer pattern applied to the student management system.
During the initialization of the system,
First, create the relevant objects.
StudentList studentList = new StudentList();
StudentListUi listUi = new StudentListUi();
StudentStatsUi statsUi = new StudentStatsUi();
Next, the two UIs indicate to the StudentList
that they are interested in being updated whenever StudentList
changes. This is also known as ‘subscribing for updates’.
studentList.addUi(listUi);
studentList.addUi(statsUi);
Within the addUi
operation of StudentList
, all Observer object subscribers are added to an internal data structure called observerList
.
// StudentList class
public void addUi(Observer o) {
observerList.add(o);
}
Now, whenever the data in StudentList
changes (e.g. when a new student is added to the StudentList
),
All interested observers are updated by calling the notifyUIs
operation.
// StudentList class
public void notifyUIs() {
// for each observer in the list
for (Observer o: observerList) {
o.update();
}
}
UIs can then pull data from the StudentList
whenever the update
operation is called.
// StudentListUI class
public void update() {
// refresh UI by pulling data from StudentList
}
Note that StudentList
is unaware of the exact nature of the two UIs but still manages to communicate with them via an intermediary.
Here is the generic description of the observer pattern:
<<Observer>>
is an interface: any class that implements it can observe an <<Observable>>
. Any number of <<Observer>>
objects can observe (i.e., listen to changes of) the <<Observable>>
object.<<Observable>>
maintains a list of <<Observer>>
objects. addObserver(Observer)
operation adds a new <<Observer>>
to the list of <<Observer>>
s.<<Observable>>
, the notifyObservers()
operation is called that will call the update()
operation of all <<Observer>>
s in the list.In a GUI application, how is the Controller notified when the “save” button is clicked? UI frameworks such as JavaFX have inbuilt support for the Observer pattern.
In a smaller system, the design of the entire system can be shown in one place.
This class diagram of se-edu/addressbook-level2 depicts the design of the entire software.
The design of bigger systems needs to be done/shown at multiple levels.
This architecture diagram of se-edu/addressbook-level3 depicts the high-level design of the software.
Here are examples of lower level designs of some components of the same software:
Multi-level design can be done in a top-down manner, bottom-up manner, or as a mix.
Agile design can be contrasted with full upfront design in the following way:
Agile designs are emergent, they’re not defined up front. Your overall system design will emerge over time, evolving to fulfill new requirements and take advantage of new technologies as appropriate. Although you will often do some initial architectural modeling at the very beginning of a project, this will be just enough to get your team going. This approach does not produce a fully documented set of models in place before you may begin coding. -- adapted from agilemodeling.com
Professional software engineers often write code using Integrated Development Environments (IDEs). IDEs support most development-related work within the same tool (hence, the term integrated).
An IDE generally consists of:
Examples of popular IDEs:
Some web-based IDEs have appeared in recent times too e.g., Amazon's Cloud9 IDE.
Some experienced developers, in particular those with a UNIX background, prefer lightweight yet powerful text editors with scripting capabilities (e.g., Emacs) over heavier IDEs.
Debugging is the process of discovering defects in the program. Here are some approaches to debugging:
Exiting process() method, x is 5.347
. This approach is not recommended due to these reasons:
Always code as if the person who ends up maintaining your code will be a violent psychopath who knows where you live. -- Martin Golding
Production code needs to be of high quality. Given how the world is becoming increasingly dependent on software, poor quality code is something no one can afford to tolerate.
Programs should be written and polished until they acquire publication quality. --Niklaus Wirth
Among various dimensions of code quality, such as run-time efficiency, security, and robustness, one of the most important is readability (aka understandability). This is because in any non-trivial software project, code needs to be read, understood, and modified by other developers later on. Even if you do not intend to pass the code to someone else, code quality is still important because you will become a 'stranger' to your own code someday.
Avoid long methods as they often contain more information than what the reader can process at a time. Consider if shortening is possible when a method goes beyond 30 . The bigger the haystack, the harder it is to find a needle.
If you need more than 3 levels of indentation, you're screwed anyway, and should fix your program. --Linux 1.3.53 Coding Style
Avoid deep nesting -- the deeper the nesting, the harder it is for the reader to keep track of the logic.
In particular, avoid arrowhead style code.
A real code example:
Bad |
|
Good |
|
Bad
| | Good
|
Avoid complicated expressions, especially those having many negations and nested parentheses. If you must evaluate complicated expressions, have it done in steps (i.e., calculate some intermediate values first and use them to calculate the final value).
Bad
return ((length < MAX_LENGTH) || (previousSize != length))
&& (typeCode == URGENT);
Good
boolean isWithinSizeLimit = length < MAX_LENGTH;
boolean isSameSize = previousSize != length;
boolean isValidCode = isWithinSizeLimit || isSameSize;
boolean isUrgent = typeCode == URGENT;
return isValidCode && isUrgent;
Bad
return ((length < MAX_LENGTH) or (previous_size != length)) and (type_code == URGENT)
Good
is_within_size_limit = length < MAX_LENGTH
is_same_size = previous_size != length
is_valid_code = is_within_size_limit or is_same_size
is_urgent = type_code == URGENT
return is_valid_code and is_urgent
The competent programmer is fully aware of the strictly limited size of his own skull; therefore he approaches the programming task in full humility, and among other things he avoids clever tricks like the plague. -- Edsger Dijkstra
Avoid magic numbers in your code. When the code has a number that does not explain the meaning of the number, it is called a "magic number" (as in "the number appears as if by magic"). Using a makes the code easier to understand because the name tells us more about the meaning of the number.
Bad
| | Good
|
Note: Python does not have a way to make a variable a constant. However, you can use a normal variable with an ALL_CAPS
name to simulate a constant.
Bad
| | Good
|
Similarly, you can have ‘magic’ values of other data types.
Bad
return "Error 1432"; // A magic string!
return "Error 1432" # A magic string!
Avoid any magic literals in general, not just magic numbers.
Make the code as explicit as possible, even if the language syntax allows them to be implicit. Here are some examples:
Java
] Use explicit type conversion instead of implicit type conversion.Java
, Python
] Use parentheses/braces to show groupings even when they can be skipped.Java
, Python
] Use enumerations when a certain variable can take only a small number of finite values. For example, instead of declaring the variable 'state' as an integer and using values 0, 1, 2 to denote the states 'starting', 'enabled', and 'disabled' respectively, declare 'state' as type SystemState
and define an enumeration SystemState
that has values 'STARTING'
, 'ENABLED'
, and 'DISABLED'
.Lay out the code so that it adheres to the logical structure. The code should read like a story. Just like how you use section breaks, chapters and paragraphs to organize a story, use classes, methods, indentation and line spacing in your code to group related segments of the code. For example, you can use blank lines to separate groups of related statements.
Sometimes, the correctness of your code does not depend on the order in which you perform certain intermediary steps. Nevertheless, this order may affect the clarity of the story you are trying to tell. Choose the order that makes the story most readable.
Bad
| | Good
|
Avoid things that would make the reader go ‘huh?’, such as,
Do not try to write ‘clever’ code. "Keep it simple, stupid” (KISS), as the old adage goes. For example, do not dismiss the brute-force yet simple solution in favor of a complicated one because of some ‘supposed benefits’ such as 'better reusability' unless you have a strong justification.
Debugging is twice as hard as writing the code in the first place. Therefore, if you write the code as cleverly as possible, you are, by definition, not smart enough to debug it. -- Brian W. Kernighan
Programs must be written for people to read, and only incidentally for machines to execute. -- Abelson and Sussman
Optimizing code prematurely has several drawbacks:
Make it work, make it right, make it fast is popular saying in the industry, which means in most cases, getting the code to perform correctly should take priority over optimizing it. If the code doesn't work correctly, it has no value no matter how fast/efficient it is.
Premature optimization is the root of all evil in programming. -- Donald Knuth
Of course, there are cases in which optimizing takes priority over other things e.g., when writing code for resource-constrained environments. This guideline is simply a caution that you should optimize only when it is really needed.
Avoid having multiple levels of abstraction within a code fragment. Note: The book The Productive Programmer (by Neal Ford) calls this the Single Level of Abstraction Principle (SLAP) while the book Clean Code (by Robert C. Martin) calls this One Level of Abstraction per Function.
Bad (readData();
and salary = basic * rise + 1000;
are at different levels of abstraction)
readData();
salary = basic * rise + 1000;
tax = (taxable ? salary * 0.07 : 0);
displayResult();
Good (all statements are at the same level of abstraction)
readData();
processData();
displayResult();
Also ensure that the code is written at the highest level of abstraction possible.
Bad (all statements are at a low levels of abstraction)
low-level statement A1
low-level statement A2
low-level statement A3
low-level statement B1
low-level statement B2
if condition X :
low-level statement C1
low-level statement C2
Good (all statements are at the same high level of abstraction)
high-level step A
high-level step B
if condition X:
high-level step C
That said, it is sometimes possible to pack two levels of abstraction into the code without affecting readability that much, provided each step in the higher-level logic is clearly marked using comments and separated (e.g., using a blank line) from adjacent steps.
Example: The following pseudocode has two levels of abstraction.
//high-level step A
low-level statement A1
low-level statement A2
low-level statement A3
//high-level step B
low-level statement B1
low-level statement B2
if condition X :
//high-level step C
low-level statement C1
low-level statement C2
The happy path should be clear and prominent in your code. Restructure the code to make the happy path (i.e., the execution path taken when everything goes well) less-nested as much as possible. It is the ‘unusual’ cases that should be nested. Someone reading the code should not get distracted by alternative paths taken when error conditions happen. One technique that could help in this regard is the use of guard clauses.
The following example shows how guard clauses can be used to reduce the nesting of the happy path.
Bad
if (!isUnusualCase) { //detecting an unusual condition
if (!isErrorCase) {
start(); //main path
process();
cleanup();
exit();
} else {
handleError();
}
} else {
handleUnusualCase(); //handling that unusual condition
}
In the code above,
Good
if (isUnusualCase) { //Guard Clause
handleUnusualCase();
return;
}
if (isErrorCase) { //Guard Clause
handleError();
return;
}
start();
process();
cleanup();
exit();
In contrast, the above code
The following pseudocode example shows how to reduce the nesting of the happy path inside a loop using a continue
statement:
Bad
| | Good
|
One essential way to improve code quality is to follow a consistent style. That is why software engineers usually follow a strict coding standard (aka style guide).
The aim of a coding standard is to make the entire codebase look like it was written by one person. A coding standard is usually specific to a programming language and specifies guidelines such as the locations of opening and closing braces, indentation styles and naming styles (e.g., whether to use Hungarian style, Pascal casing, Camel casing, etc.). It is important that the whole team/company uses the same coding standard and that the standard is generally not inconsistent with typical industry practices. If a company's coding standard is very different from what is typically used in the industry, new recruits will take longer to get used to the company's coding style.
IDEs can help to enforce some parts of a coding standard e.g., indentation rules.
Go through the Java coding standard at @SE-EDU and learn the basic style rules.
Sample coding standard: PEP 8 Python Style Guide -- by Python.org
Go through the Java coding standard at @SE-EDU and learn the intermediate style rules.
Every system is built from a domain-specific language designed by the programmers to describe that system. Functions are the verbs of that language, and classes are the nouns.
-- Robert C. Martin, Clean Code: A Handbook of Agile Software Craftsmanship
Use nouns for classes/variables and verbs for methods/functions.
Name for a | Bad | Good |
---|---|---|
Class | CheckLimit | LimitChecker |
Method | result() | calculate() |
Distinguish clearly between single-valued and multi-valued variables.
Good
Person student;
ArrayList<Person> students;
Good
name = 'Jim'
names = ['Jim', 'Alice']
A name is not just for differentiation; it should explain the named entity to the reader accurately and at a sufficient level of detail.
Bad | Good |
---|---|
processInput() (what 'process'?) | removeWhiteSpaceFromInput() |
flag | isValidInput |
temp |
If a name has multiple words, they should be in a sensible order.
Bad | Good |
---|---|
bySizeOrder() | orderBySize() |
Imagine going to the doctor's and saying "My eye1 is swollen"! Don’t use numbers or case to distinguish names.
Bad | Bad | Good |
---|---|---|
value1 , value2 | value , Value | originalValue , finalValue |
While it is preferable not to have lengthy names, names that are 'too short' are even worse. If you must abbreviate or use acronyms, do it consistently. Explain their full meaning at an obvious location.
Related things should be named similarly, while unrelated things should NOT.
Example: Consider these variables
colorBlack
: hex value for color blackcolorWhite
: hex value for color whitecolorBlue
: number of times blue is usedhexForRed
: hex value for color redThis is misleading because colorBlue
is named similar to colorWhite
and colorBlack
but has a different purpose while hexForRed
is named differently but has a very similar purpose to the first two variables. The following is better:
hexForBlack
hexForWhite
hexForRed
blueColorCount
Avoid misleading or ambiguous names (e.g., those with multiple meanings), similar sounding names, hard-to-pronounce ones (e.g., avoid ambiguities like "is that a lowercase L, capital I or number 1?", or "is that number 0 or letter O?"), almost similar names.
Bad | Good | Reason |
---|---|---|
phase0 | phaseZero | Is that zero or letter O? |
rwrLgtDirn | rowerLegitDirection | Hard to pronounce |
right left wrong | rightDirection leftDirection wrongResponse | right is for 'correct' or 'opposite of 'left'? |
redBooks readBooks | redColorBooks booksRead | red and read (past tense) sounds the same |
FiletMignon | egg | If the requirement is just a name of a food, egg is a much easier to type/say choice than FiletMignon |
Always include a default branch in case
statements. This ensures that all possible outcomes have been considered at the branching point.
Furthermore, use the default
branch for the intended default action and not just to execute the last option. If there is no default action, you can use the default
branch to detect errors (i.e., if execution reached the default
branch, raise a suitable error). This also applies to the final else
of an if-else
construct. That is, the final else
should mean 'everything else', and not the final option. Do not use else
when an if
condition can be explicitly specified, unless there is absolutely no other possibility.
Bad
| | Good
|
Bad
double computeRectangleArea(double length, double width) {
length = length * width; // parameter reused as a variable
return length;
}
def compute_rectangle_area(length, width):
length = length * width
return length
Good
double computeRectangleArea(double length, double width) {
double area;
area = length * width;
return area;
}
def compute_rectangle_area(length, width):
area = length * width
return area
}
Avoid empty catch
statements, as they are a way to ignore errors silently (which is not a good thing). In cases when it is unavoidable, at least give a comment to explain why the catch
block is left empty.
Get rid of unused code the moment it becomes redundant. You might feel reluctant to delete code you have painstakingly written, even if you have no use for that code anymore ("I spent a lot of time writing that code; what if I need it again?"). Consider all code as baggage you have to carry. If you need that code again, simply recover it from the revision control tool you are using. Deleting code you wrote previously is a sign that you are improving.
Minimize global variables. Global variables may be the most convenient way to pass information around, but they do create implicit links between code segments that use the global variable. Avoid them as much as possible.
Define variables in the least possible scope. For example, if the variable is used only within the if
block of the conditional statement, it should be declared inside that if
block.
The most powerful technique for minimizing the scope of a local variable is to declare it where it is first used. -- Effective Java, by Joshua Bloch
Code duplication, especially when you copy-paste-modify code, often indicates a poor quality implementation. While it may not be possible to have zero duplication, always think twice before duplicating code; most often there is a better alternative.
This guideline is closely related to the DRY Principle.
Good code is its own best documentation. As you’re about to add a comment, ask yourself, ‘How can I improve the code so that this comment isn’t needed?’ Improve the code and then document it to make it even clearer. -- Steve McConnell, Author of Clean Code
Some think commenting heavily increases the 'code quality'. That is not so. Avoid writing comments to explain bad code. Improve the code to make it self-explanatory.
Do not repeat in comments information that is already obvious from the code. If the code is self-explanatory, a comment may not be needed.
Bad
//increment x
x++;
//trim the input
trimInput();
Bad
# increment x
x = x + 1
# trim the input
trim_input()
Write comments targeting other programmers reading the code. Do not write comments as if they are private notes to yourself. Instead, One type of comment that is almost always useful is the header comment that you write for a class or an operation to explain its purpose.
Bad Reason: this comment will only make sense to the person who wrote it
// a quick trim function used to fix bug I detected overnight
void trimInput() {
....
}
Good
/** Trims the input of leading and trailing spaces */
void trimInput() {
....
}
Bad Reason: this comment will only make sense to the person who wrote it
def trim_input():
"""a quick trim function used to fix bug I detected overnight"""
...
Good
def trim_input():
"""Trim the input of leading and trailing spaces"""
...
Comments should explain the WHAT and WHY aspects of the code, rather than the HOW aspect.
WHAT: The specification of what the code is supposed to do. The reader can compare such comments to the implementation to verify if the implementation is correct.
Example: This method is possibly buggy because the implementation does not seem to match the comment. In this case, the comment could help the reader to detect the bug.
/** Removes all spaces from the {@code input} */
void compact(String input) {
input.trim();
}
WHY: The rationale for the current implementation.
Example: Without this comment, the reader will not know the reason for calling this method.
// Remove spaces to comply with IE23.5 formatting rules
compact(input);
HOW: The explanation for how the code works. This should already be apparent from the code, if the code is self-explanatory. Adding comments to explain the same thing is redundant.
Example:
Bad Reason: Comment explains how the code works.
// return true if both left end and right end are correct
// or the size has not incremented
return (left && right) || (input.size() == size);
Good Reason: The code is now self-explanatory -- the comment is no longer needed.
boolean isSameSize = (input.size() == size);
return (isLeftEndCorrect && isRightEndCorrect) || isSameSize;
The process of restructuring code in small steps without modifying its external behavior is called refactoring. Refactoring is needed because the first version of the code you write may not be of production quality. It is OK to first concentrate on making the code work, rather than worry over the quality of the code, as long as you improve the quality later.
Refactoring code can have many secondary benefits e.g.
Given below are two common refactorings (more).
Refactoring Name: Consolidate Duplicate Conditional Fragments
Situation: The same fragment of code is in all branches of a conditional expression.
Method: Move it outside of the expression.
Example:
| → |
|
| → |
|
Refactoring Name: Extract Method
Situation: You have a code fragment that can be grouped together.
Method: Turn the fragment into a method whose name explains the purpose of the method.
Example:
void printOwing() {
printBanner();
// print details
System.out.println("name: " + name);
System.out.println("amount " + getOutstanding());
}
void printOwing() {
printBanner();
printDetails(getOutstanding());
}
void printDetails(double outstanding) {
System.out.println("name: " + name);
System.out.println("amount " + outstanding);
}
def print_owing():
print_banner()
# print details
print("name: " + name)
print("amount " + get_outstanding())
def print_owing():
print_banner()
print_details(get_outstanding())
def print_details(amount):
print("name: " + name)
print("amount " + amount)
Some IDEs have builtin support for basic refactorings such as automatically renaming a variable/method/class in all places it has been used.
Refactoring, even if done with the aid of an IDE, may still result in regressions. Therefore, each small refactoring should be followed by regression testing.
There are refactoring catalogs listing various refactorings. Given below are some commonly used refactorings.
One way to identify refactoring opportunities is by code smells.
A code smell is a surface indication that usually corresponds to a deeper problem in the system. First, a smell is by definition something that's quick to spot. Second, smells don't always indicate a problem.
--adapted from https://martinfowler.com/bliki/CodeSmell.html
An example (from the same source as above) is the code smell data class i.e., a class with all data and no behavior. When you encounter the such a class, you can explore if refactoring it to move the corresponding behavior into that class is appropriate. Some more examples:
Periodic refactoring is a good way to pay off the technical debt a codebase has accumulated.
Software systems are prone to the build up of cruft - deficiencies in internal quality that make it harder than it would ideally be to modify and extend the system further. Technical Debt is a metaphor, coined by Ward Cunningham, that frames how to think about dealing with this cruft, thinking of it like a financial debt. The extra effort that it takes to add new features is the interest paid on the debt.
--https://martinfowler.com/bliki/TechnicalDebt.html
While it is important to refactor frequently so as to avoid the accumulation of ‘messy’ code (aka technical debt), an important question is how much refactoring is too much refactoring? It is too much refactoring when the benefits no longer justify the cost. The costs and the benefits depend on the context. That is why some refactorings are ‘opposites’ of each other (e.g., extract method vs inline method).
Developer-to-developer documentation can be in one of two forms:
Another view proposed by Daniele Procida in this article is as follows:
There is a secret that needs to be understood in order to write good software documentation: there isn’t one thing called documentation, there are four. They are: tutorials, how-to guides, explanation and technical reference. They represent four different purposes or functions, and require four different approaches to their creation. Understanding the implications of this will help improve most software documentation - often immensely. ...
TUTORIALS
A tutorial:
- is learning-oriented
- allows the newcomer to get started
- is a lesson
Analogy: teaching a small child how to cook
HOW-TO GUIDES
A how-to guide:
- is goal-oriented
- shows how to solve a specific problem
- is a series of steps
Analogy: a recipe in a cookery book
EXPLANATION
An explanation:
- is understanding-oriented
- explains
- provides background and context
Analogy: an article on culinary social history
REFERENCE
A reference guide:
- is information-oriented
- describes the machinery
- is accurate and complete
Analogy: a reference encyclopedia article
Software documentation (applies to both user-facing and developer-facing) is best kept in a text format for ease of version tracking. A writer-friendly source format is also desirable as non-programmers (e.g., technical writers) may need to author/edit such documents. As a result, formats such as Markdown, AsciiDoc, and PlantUML are often used for software documentation.
When writing project documents, a top-down breadth-first explanation is easier to understand than a bottom-up one.
The main advantage of the top-down approach is that the document is structured like an upside down tree (root at the top) and the reader can travel down a path she is interested in until she reaches the component she is interested to learn in-depth, without having to read the entire document or understand the whole system.
To explain a system called SystemFoo
with two sub-systems, FrontEnd
and BackEnd
, start by describing the system at the highest level of abstraction, and progressively drill down to lower level details. An outline for such a description is given below.
[First, explain what the system is, in a black-box fashion (no internal details, only the external view).]
SystemFoo
is a ....
[Next, explain the high-level architecture of SystemFoo
, referring to its major components only.]
SystemFoo
consists of two major components:FrontEnd
andBackEnd
.
The job ofFrontEnd
is to ... while the job ofBackEnd
is to ...
And this is howFrontEnd
andBackEnd
work together ...
[Now you can drill down to FrontEnd
's details.]
FrontEnd
consists of three major components:A
,B
,C
A
's job is to ...B
's job is to...C
's job is to...
And this is how the three components work together ...
[At this point, further drill down to the internal workings of each component. A reader who is not interested in knowing the nitty-gritty details can skip ahead to the section on BackEnd
.]
In-depth description of
A
In-depth description ofB
...
[At this point drill down to the details of the BackEnd
.]
...
Technical documents exist to help others understand technical details. Therefore, it is not enough for the documentation to be accurate and comprehensive; it should also be comprehensible.
Here are some tips on writing effective documentation.
Aim for 'just enough' developer documentation.
Anything that is already clear in the code need not be described in words. Instead, focus on providing higher level information that is not readily visible in the code or comments.
Refrain from duplicating chunks of text. When describing several similar algorithms/designs/APIs, etc., do not simply duplicate large chunks of text. Instead, describe the similarities in one place and emphasize only the differences in other places. It is very annoying to see pages and pages of similar text without any indication as to how they differ from each other.
JavaDoc is a tool for generating API documentation in HTML format from comments in the source code. In addition, modern IDEs use JavaDoc comments to generate explanatory tooltips.
An example method header comment in JavaDoc format:
/**
* Returns an Image object that can then be painted on the screen.
* The url argument must specify an absolute {@link URL}. The name
* argument is a specifier that is relative to the url argument.
* <p>
* This method always returns immediately, whether or not the
* image exists. When this applet attempts to draw the image on
* the screen, the data will be loaded. The graphics primitives
* that draw the image will incrementally paint on the screen.
*
* @param url An absolute URL giving the base location of the image.
* @param name The location of the image, relative to the url argument.
* @return The Image at the specified URL.
* @see Image
*/
public Image getImage(URL url, String name) {
try {
return getImage(new URL(url, name));
} catch (MalformedURLException e) {
return null;
}
}
Generated HTML documentation:
Tooltip generated by IntelliJ IDE:
In the absence of more extensive guidelines (e.g., given in a coding standard adopted by your project), you can follow the two examples below in your code.
A minimal JavaDoc comment example for methods:
/**
* Returns lateral location of the specified position.
* If the position is unset, NaN is returned.
*
* @param x X coordinate of position.
* @param y Y coordinate of position.
* @param zone Zone of position.
* @return Lateral location.
* @throws IllegalArgumentException If zone is <= 0.
*/
public double computeLocation(double x, double y, int zone)
throws IllegalArgumentException {
// ...
}
A minimal JavaDoc comment example for classes:
package ...
import ...
/**
* Represents a location in a 2D space. A <code>Point</code> object corresponds to
* a coordinate represented by two integers e.g., <code>3,6</code>
*/
public class Point {
// ...
}
Well-written applications include error-handling code that allows them to recover gracefully from unexpected errors. When an error occurs, the application may need to request user intervention, or it may be able to recover on its own. In extreme cases, the application may log the user off or shut down the system. -- Microsoft
Exceptions are used to deal with 'unusual' but not entirely unexpected situations that the program might encounter at runtime.
Exception:
The term exception is shorthand for the phrase "exceptional event." An exception is an event, which occurs during the execution of a program, that disrupts the normal flow of the program's instructions. –- Java Tutorial (Oracle Inc.)
Examples:
Most languages allow code that encountered an "exceptional" situation to encapsulate details of the situation in an Exception object and throw/raise that object so that another piece of code can catch it and deal with it. This is especially useful when the code that encountered the unusual situation does not know how to deal with it.
The extract below from the -- Java Tutorial (with slight adaptations) explains how exceptions are typically handled.
When an error occurs at some point in the execution, the code being executed creates an exception object and hands it off to the runtime system. The exception object contains information about the error, including its type and the state of the program when the error occurred. Creating an exception object and handing it to the runtime system is called throwing an exception.
After a method throws an exception, the runtime system attempts to find something to handle it in the . The runtime system searches the call stack for a method that contains a block of code that can handle the exception. This block of code is called an exception handler. The search begins with the method in which the error occurred and proceeds through the call stack in the reverse order in which the methods were called. When an appropriate handler is found, the runtime system passes the exception to the handler. An exception handler is considered appropriate if the type of the exception object thrown matches the type that can be handled by the handler.
The exception handler chosen is said to catch the exception. If the runtime system exhaustively searches all the methods on the call stack without finding an appropriate exception handler, the program terminates.
Advantages of exception handling in this way:
Assertions are used to define assumptions about the program state so that the runtime can verify them. An assertion failure indicates a possible bug in the code because the code has resulted in a program state that violates an assumption about how the code should behave.
An assertion can be used to express something like when the execution comes to this point, the variable v
cannot be null.
If the runtime detects an assertion failure, it typically takes some drastic action such as terminating the execution with an error message. This is because an assertion failure indicates a possible bug and the sooner the execution stops, the safer it is.
In the Java code below, suppose you set an assertion that timeout
returned by Config.getTimeout()
is greater than 0
. Now, if Config.getTimeout()
returns -1
in a specific execution of this line, the runtime can detect it as an assertion failure -- i.e., an assumption about the expected behavior of the code turned out to be wrong which could potentially be the result of a bug -- and take some drastic action such as terminating the execution.
int timeout = Config.getTimeout();
// set assertion here ...
Use the assert
keyword to define assertions.
This assertion will fail with the message x should be 0
if x
is not 0 at this point.
x = getX();
assert x == 0 : "x should be 0";
...
Assertions can be disabled without modifying the code.
java -enableassertions HelloWorld
(or java -ea HelloWorld
) will run HelloWorld
with assertions enabled while java -disableassertions HelloWorld
will run it without verifying assertions.
Java disables assertions by default. This could create a situation where you think all assertions are being verified as true
while in fact they are not being verified at all. Therefore, remember to enable assertions when you run the program if you want them to be in effect.
Enable assertions in IntelliJ (how?) and get an assertion to fail temporarily (e.g. insert an assert false
into the code temporarily) to confirm assertions are being verified.
Java assert
vs JUnit assertions: Both check for a given condition but JUnit assertions are more powerful and customized for testing. In addition, JUnit assertions are not disabled by default. Use JUnit assertions in test code and Java assert
in functional code.
It is recommended that assertions be used liberally in the code. Their impact on performance is low, and worth the additional safety they provide.
Do not use assertions to do work because assertions can be disabled. If not, your program will stop working when assertions are not enabled.
The code below will not invoke the writeFile()
method when assertions are disabled. If that method is performing some work that is necessary for your program, your program will not work correctly when assertions are disabled.
...
assert writeFile() : "File writing is supposed to return true";
Assertions are suitable for verifying assumptions about Internal Invariants, Control-Flow Invariants, Preconditions, Postconditions, and Class Invariants. Refer to Programming with Assertions (second half) to learn more.
Exceptions and assertions are two complementary ways of handling errors in software but they serve different purposes. Therefore, both assertions and exceptions should be used in code.
Logging is the deliberate recording of certain information during a program execution for future reference. Logs are typically written to a log file but it is also possible to log information in other ways e.g. into a database or a remote server.
Logging can be useful for troubleshooting problems. A good logging system records some system information regularly. When bad things happen to a system e.g. an unanticipated failure, their associated log files may provide indications of what went wrong and actions can then be taken to prevent it from happening again.
A log file is like the of an airplane; they don't prevent problems but they can be helpful in understanding what went wrong after the fact.
source: https://commons.wikimedia.org
Most programming environments come with logging systems that allow sophisticated forms of logging. They have features such as the ability to enable and disable logging easily or to change the logging .
This sample Java code uses Java’s default logging mechanism.
First, import the relevant Java package:
import java.util.logging.*;
Next, create a Logger
:
private static Logger logger = Logger.getLogger("Foo");
Now, you can use the Logger
object to log information. Note the use of a for each message. When running the code, the logging level can be set to WARNING
so that log messages specified as having INFO
level (which is a lower level than WARNING
) will not be written to the log file at all.
// log a message at INFO level
logger.log(Level.INFO, "going to start processing");
// ...
processInput();
if (error) {
// log a message at WARNING level
logger.log(Level.WARNING, "processing error", ex);
}
// ...
logger.log(Level.INFO, "end of processing");
A defensive programmer codes under the assumption "if you leave room for things to go wrong, they will go wrong". Therefore, a defensive programmer proactively tries to eliminate any room for things to go wrong.
Consider a method MainApp#getConfig()
that returns a Config
object containing configuration data. A typical implementation is given below:
class MainApp {
Config config;
/** Returns the config object */
Config getConfig() {
return config;
}
}
If the returned Config
object is not meant to be modified, a defensive programmer might use a more defensive implementation given below. This is more defensive because even if the returned Config
object is modified (although it is not meant to be), it will not affect the config
object inside the MainApp
object.
/** Returns a copy of the config object */
Config getConfig() {
return config.copy(); // return a defensive copy
}
Consider two classes, Account
and Guarantor
, with an association as shown in the following diagram:
Example:
Here, the association is compulsory i.e., an Account
object should always be linked to a Guarantor
. One way to implement this is to simply use a reference variable, like this:
class Account {
Guarantor guarantor;
void setGuarantor(Guarantor g) {
guarantor = g;
}
}
However, what if someone else used the Account
class like this?
Account a = new Account();
a.setGuarantor(null);
This results in an Account
without a Guarantor
! In a real banking system, this could have serious consequences! The code here did not try to prevent such a thing from happening. You can make the code more defensive by proactively enforcing the multiplicity constraint, like this:
class Account {
private Guarantor guarantor;
public Account(Guarantor g) {
if (g == null) {
stopSystemWithMessage(
"multiplicity violated. Null Guarantor");
}
guarantor = g;
}
public void setGuarantor(Guarantor g) {
if (g == null) {
stopSystemWithMessage(
"multiplicity violated. Null Guarantor");
}
guarantor = g;
}
// ...
}
It is not necessary to be 100% defensive all the time. While defensive code may be less prone to be misused or abused, such code can also be more complicated and slower to run.
The suitable degree of defensiveness depends on many factors such as:
In terms of timing and frequency, there are two general approaches to integration: late and one-time, early and frequent.
Late and one-time: wait till all components are completed and integrate all finished components near the end of the project.
This approach is not recommended because integration often causes many component incompatibilities (due to previous miscommunications and misunderstandings) to surface which can lead to delivery delays i.e., Late integration → incompatibilities found → major rework required → cannot meet the delivery date.
Early and frequent: integrate early and evolve each part in parallel, in small steps, re-integrating frequently.
A can be written first. This can be done by one developer, possibly the one in charge of integration. After that, all developers can flesh out the skeleton in parallel, adding one feature at a time. After each feature is done, simply integrate the new code into the main system.
Big-bang integration: integrate all (or too many) components at the same time. More generally, integrating too many changes at the same time.
Big-bang is not recommended because it will uncover too many problems at the same time which could make debugging and bug-fixing more complex than when problems are uncovered incrementally.
Incremental integration: integrate a few components at a time. More generally, integrating changes gradually. This approach is better than big-bang integration because it surfaces integration problems in a more manageable way.
Build automation tools automate the steps of the build process, usually by means of build scripts.
In a non-trivial project, building a product from its source code can be a complex multistep process. For example, it can include steps such as: pull code from the revision control system, compile, link, run automated tests, automatically update release documents (e.g., build number), package into a distributable, push to repo, deploy to a server, delete temporary files created during building/testing, email developers of the new build, and so on. Furthermore, this build process can be done ‘on demand’, it can be scheduled (e.g., every day at midnight) or it can be triggered by various events (e.g., triggered by a code push to the revision control system).
Some of these build steps such as compiling, linking and packaging, are already automated in most modern IDEs. For example, several steps happen automatically when the ‘build’ button of the IDE is clicked. Some IDEs even allow customization of this build process to some extent.
However, most big projects use specialized build tools to automate complex build processes.
Some popular build tools relevant to Java developers: Gradle, Maven, Apache Ant, GNU Make
Some other build tools: Grunt (JavaScript), Rake (Ruby)
Some build tools also serve as dependency management tools. Modern software projects often depend on third party libraries that evolve constantly. That means developers need to download the correct version of the required libraries and update them regularly. Therefore, dependency management is an important part of build automation. Dependency management tools can automate that aspect of a project.
Maven and Gradle, in addition to managing the build process, can play the role of dependency management tools too.
An extreme application of build automation is called continuous integration (CI) in which integration, building, and testing happens automatically after each code change.
A natural extension of CI is Continuous Deployment (CD) where the changes are not only integrated continuously, but also deployed to end-users at the same time.
Some examples of CI/CD tools: Travis, Jenkins, Appveyor, CircleCI, GitHub Actions
Reuse is a major theme in software engineering practices. By reusing tried-and-tested components, the robustness of a new software system can be enhanced while reducing the manpower and time requirement. Reusable components come in many forms; it can be reusing a piece of code, a subsystem, or a whole software.
While you may be tempted to use many libraries/frameworks/platforms that seem to crop up on a regular basis and promise to bring great benefits, note that there are costs associated with reuse. Here are some:
An Application Programming Interface (API) specifies the interface through which other programs can interact with a software component. It is a contract between the component and its clients.
A class has an API (e.g., API of the Java String
class, API of the Python str
class) which is a collection of public methods that you can invoke to make use of the class.
The GitHub API is a collection of web request formats that the GitHub server accepts and their corresponding responses. You can write a program that interacts with GitHub through that API.
When developing large systems, if you define the API of each component early, the development team can develop the components in parallel because the future behavior of the other components are now more predictable.
A library is a collection of modular code that is general and can be used by other programs.
Java classes you get with the JDK (such as String
, ArrayList
, HashMap
, etc.) are library classes that are provided in the default Java distribution.
Natty is a Java library that can be used for parsing strings that represent dates e.g., The 31st of April in the year 2008
built-in modules you get with Python (such as csv
, random
, sys
, etc.) are libraries that are provided in the default Python distribution. Classes such as list
, str
, dict
are built-in library classes that you get with Python.
Colorama is a Python library that can be used for colorizing text in a CLI.
These are the typical steps required to use a library:
The overall structure and execution flow of a specific category of software systems can be very similar. The similarity is an opportunity to reuse at a high scale.
Running example:
IDEs for different programming languages are similar in how they support editing code, organizing project files, debugging, etc.
A software framework is a reusable implementation of a software (or part thereof) providing generic functionality that can be selectively customized to produce a specific application.
Running example:
Eclipse is an IDE framework that can be used to create IDEs for different programming languages.
Some frameworks provide a complete implementation of a default behavior which makes them immediately usable.
Running example:
Eclipse is a fully functional Java IDE out-of-the-box.
A framework facilitates the adaptation and customization of some desired functionality.
Running example:
The Eclipse plugin system can be used to create an IDE for different programming languages while reusing most of the existing IDE features of Eclipse.
e.g., https://marketplace.eclipse.org/content/pydev-python-ide-eclipse
Some frameworks cover only a specific component or an aspect.
JavaFX is a framework for creating Java GUIs. Tkinter is a GUI framework for Python.
More examples of frameworks
Although both frameworks and libraries are reuse mechanisms, there are notable differences:
Libraries are meant to be used ‘as is’ while frameworks are meant to be customized/extended. e.g., writing plugins for Eclipse so that it can be used as an IDE for different languages (C++, PHP, etc.), adding modules and themes to Drupal, and adding test cases to JUnit.
Your code calls the library code while the framework code calls your code. Frameworks use a technique called inversion of control, aka the “Hollywood principle” (i.e., don’t call us, we’ll call you!). That is, you write code that will be called by the framework, e.g., writing test methods that will be called by the JUnit framework. In the case of libraries, your code calls libraries.
A platform provides a runtime environment for applications. A platform is often bundled with various libraries, tools, frameworks, and technologies in addition to a runtime environment but the defining characteristic of a software platform is the presence of a runtime environment.
Technically, an operating system can be called a platform. For example, Windows PC is a platform for desktop applications while iOS is a platform for mobile applications.
Two well-known examples of platforms are JavaEE and .NET, both of which sit above the operating systems layer, and are used to develop enterprise applications. Infrastructure services such as connection pooling, load balancing, remote code execution, transaction management, authentication, security, messaging etc. are done similarly in most enterprise applications. Both JavaEE and .NET provide these services to applications in a customizable way without developers having to implement them from scratch every time.
Software Quality Assurance (QA) is the process of ensuring that the software being built has the required levels of quality.
While testing is the most common activity used in QA, there are other complementary techniques such as static analysis, code reviews, and formal verification.
Quality Assurance = Validation + Verification
QA involves checking two aspects:
Whether something belongs under validation or verification is not that important. What is more important is that both are done, instead of limiting to only verification (i.e., remember that the requirements can be wrong too).
Code review is the systematic examination of code with the intention of finding where the code can be improved.
Reviews can be done in various forms. Some examples below:
Pull Request reviews
In pair programming
Formal inspections
Inspections involve a group of people systematically examining project artifacts to discover defects. Members of the inspection team play various roles during the process, such as:
Advantages of code review over testing:
Disadvantages:
Static analysis: Static analysis is the analysis of code without actually executing the code.
Static analysis of code can find useful information such as unused variables, unhandled exceptions, style errors, and statistics. Most modern IDEs come with some inbuilt static analysis capabilities. For example, an IDE can highlight unused variables as you type the code into the editor.
The term static in static analysis refers to the fact that the code is analyzed without executing the code. In contrast, dynamic analysis requires the code to be executed to gather additional information about the code e.g., performance characteristics.
Higher-end static analysis tools (static analyzers) can perform more complex analysis such as locating potential bugs, memory leaks, inefficient code structures, etc.
Some example static analyzers for Java: CheckStyle, PMD, FindBugs
Linters are a subset of static analyzers that specifically aim to locate areas where the code can be made 'cleaner'.
Formal verification uses mathematical techniques to prove the correctness of a program.
Advantages:
Disadvantages:
Testing: Operating a system or component under specified conditions, observing or recording the results, and making an evaluation of some aspect of the system or component. –- source: IEEE
When testing, you execute a set of test cases. A test case specifies how to perform a test. At a minimum, it specifies the input to the software under test (SUT) and the expected behavior.
Example: A minimal test case for testing a browser:
longfile.html
located in the test data
folder.longfile.html
.Test cases can be determined based on the specification, reviewing similar existing systems, or comparing to the past behavior of the SUT.
For each test case you should do the following:
A test case failure is a mismatch between the expected behavior and the actual behavior. A failure indicates a potential defect (or a bug) -- we say 'potential' because the error could be in the test case itself.
Example: In the browser example above, a test case failure is implied if the scrollbar remains disabled after loading longfile.html
. The defect/bug causing that failure could be an uninitialized variable.
Testability is an indication of how easy it is to test an SUT. As testability depends a lot on the design and implementation, you should try to increase the testability when you design and implement software. The higher the testability, the easier it is to achieve better quality software.
When you modify a system, the modification may result in some unintended and undesirable effects on the system. Such an effect is called a regression.
Regression testing is the re-testing of the software to detect regressions. The typical way to detect regressions is retesting all related components, even if they had been tested before.
Regression testing is more effective when it is done frequently, after each small change. However, doing so can be prohibitively expensive if testing is done manually. Hence, regression testing is more practical when it is automated.
Developer testing is the testing done by the developers themselves as opposed to dedicated testers or end-users.
Delaying testing until the full product is complete has a number of disadvantages:
Therefore, it is better to do early testing, as hinted by the popular rule of thumb given below, also illustrated by the graph below it.
The earlier a bug is found, the easier and cheaper to have it fixed.
Such early testing software is usually, and often by necessity, done by the developers themselves i.e., developer testing.
Unit testing: testing individual units (methods, classes, subsystems, ...) to ensure each piece works correctly.
In OOP code, it is common to write one or more unit tests for each public method of a class.
Here are the code skeletons for a Foo
class containing two methods and a FooTest
class that contains unit tests for those two methods.
class Foo {
String read() {
// ...
}
void write(String input) {
// ...
}
}
class FooTest {
@Test
void read() {
// a unit test for Foo#read() method
}
@Test
void write_emptyInput_exceptionThrown() {
// a unit tests for Foo#write(String) method
}
@Test
void write_normalInput_writtenCorrectly() {
// another unit tests for Foo#write(String) method
}
}
import unittest
class Foo:
def read(self):
# ...
def write(self, input):
# ...
class FooTest(unittest.TestCase):
def test_read(self):
# a unit test for read() method
def test_write_emptyIntput_ignored(self):
# a unit test for write(string) method
def test_write_normalInput_writtenCorrectly(self):
# another unit test for write(string) method
A proper unit test requires the unit to be tested in isolation so that bugs in the cannot influence the test i.e., bugs outside of the unit should not affect the unit tests.
If a Logic
class depends on a Storage
class, unit testing the Logic
class requires isolating the Logic
class from the Storage
class.
Stubs can isolate the from its dependencies.
Stub: A stub has the same interface as the component it replaces, but its implementation is so simple that it is unlikely to have any bugs. It mimics the responses of the component, but only for a limited set of predetermined inputs. That is, it does not know how to respond to any other inputs. Typically, these mimicked responses are hard-coded in the stub rather than computed or retrieved from elsewhere, e.g., from a database.
Consider the code below:
class Logic {
Storage s;
Logic(Storage s) {
this.s = s;
}
String getName(int index) {
return "Name: " + s.getName(index);
}
}
interface Storage {
String getName(int index);
}
class DatabaseStorage implements Storage {
@Override
public String getName(int index) {
return readValueFromDatabase(index);
}
private String readValueFromDatabase(int index) {
// retrieve name from the database
}
}
Normally, you would use the Logic
class as follows (note how the Logic
object depends on a DatabaseStorage
object to perform the getName()
operation):
Logic logic = new Logic(new DatabaseStorage());
String name = logic.getName(23);
You can test it like this:
@Test
void getName() {
Logic logic = new Logic(new DatabaseStorage());
assertEquals("Name: John", logic.getName(5));
}
However, this logic
object being tested is making use of a DataBaseStorage
object which means a bug in the DatabaseStorage
class can affect the test. Therefore, this test is not testing Logic
in isolation from its dependencies and hence it is not a pure unit test.
Here is a stub class you can use in place of DatabaseStorage
:
class StorageStub implements Storage {
@Override
public String getName(int index) {
if (index == 5) {
return "Adam";
} else {
throw new UnsupportedOperationException();
}
}
}
Note how the StorageStub
has the same interface as DatabaseStorage
, but is so simple that it is unlikely to contain bugs, and is pre-configured to respond with a hard-coded response, presumably, the correct response DatabaseStorage
is expected to return for the given test input.
Here is how you can use the stub to write a unit test. This test is not affected by any bugs in the DatabaseStorage
class and hence is a pure unit test.
@Test
void getName() {
Logic logic = new Logic(new StorageStub());
assertEquals("Name: Adam", logic.getName(5));
}
In addition to Stubs, there are other type of replacements you can use during testing, e.g., Mocks, Fakes, Dummies, Spies.
Integration testing : testing whether different parts of the software work together (i.e., integrates) as expected. Integration tests aim to discover bugs in the 'glue code' related to how components interact with each other. These bugs are often the result of misunderstanding what the parts are supposed to do vs what the parts are actually doing.
Suppose a class Car
uses classes Engine
and Wheel
. If the Car
class assumed a Wheel
can support a speed of up to 200 mph but the actual Wheel
can only support a speed of up to 150 mph, it is the integration test that is supposed to uncover this discrepancy.
Integration testing is not simply a case of repeating the unit test cases using the actual dependencies (instead of the stubs used in unit testing). Instead, integration tests are additional test cases that focus on the interactions between the parts.
Suppose a class Car
uses classes Engine
and Wheel
. Here is how you would go about doing pure integration tests:
a) First, unit test Engine
and Wheel
.
b) Next, unit test Car
in isolation of Engine
and Wheel
, using stubs for Engine
and Wheel
.
c) After that, do an integration test for Car
by using it together with the Engine
and Wheel
classes to ensure that Car
integrates properly with the Engine
and the Wheel
.
In practice, developers often use a hybrid of unit+integration tests to minimize the need for stubs.
Here's how a hybrid unit+integration approach could be applied to the same example used above:
(a) First, unit test Engine
and Wheel
.
(b) Next, unit test Car
in isolation of Engine
and Wheel
, using stubs for Engine
and Wheel
.
(c) After that, do an integration test for Car
by using it together with the Engine
and Wheel
classes to ensure that Car
integrates properly with the Engine
and the Wheel
. This step should include test cases that are meant to unit test Car
(i.e., test cases used in the step (b) of the example above) as well as test cases that are meant to test the integration of Car
with Wheel
and Engine
(i.e., pure integration test cases used of the step (c) in the example above).
Note that you no longer need stubs for Engine
and Wheel
. The downside is that Car
is never tested in isolation of its dependencies. Given that its dependencies are already unit tested, the risk of bugs in Engine
and Wheel
affecting the testing of Car
can be considered minimal.
System testing: take the whole system and test it against the system specification.
System testing is typically done by a testing team (also called a QA team).
System test cases are based on the specified external behavior of the system. Sometimes, system tests go beyond the bounds defined in the specification. This is useful when testing that the system fails 'gracefully' when pushed beyond its limits.
Suppose the SUT is a browser that is supposedly capable of handling web pages containing up to 5000 characters. Given below is a test case to test if the SUT fails gracefully if pushed beyond its limits.
Test case: load a web page that is too big
* Input: loads a web page containing more than 5000 characters.
* Expected behavior: aborts the loading of the page
and shows a meaningful error message.
This test case would fail if the browser attempted to load the large file anyway and crashed.
System testing includes testing against non-functional requirements too. Here are some examples:
Alpha testing is performed by the users, under controlled conditions set by the software development team.
Beta testing is performed by a selected subset of target users of the system in their natural work setting.
An open beta release is the release of not-yet-production-quality-but-almost-there software to the general population. For example, Google’s Gmail was in 'beta' for many years before the label was finally removed.
Dogfooding is when creators use their own product in order to experience how end users experience the product. The term is supposedly derived from the phrase "eating our own dogfood". Dogfooding is different from regular testing in that you become an end user, rather than pretend to be an end user.
For example, suppose a company produces an email client software. Then, getting some of the employees to use that software for their day-to-day emailing would be dogfooding. Such longer-term, consistent, and authentic use of the software can point to areas of improvement that regular testing (which is often short-term and 'simulated') might not encounter.
Note that dogfooding to be useful, observations need to be deliberately collected and processed i.e., just using the product itself is not enough.
Here are two alternative approaches to testing a software: Scripted testing and Exploratory testing.
Scripted testing: First write a set of test cases based on the expected behavior of the SUT, and then perform testing based on that set of test cases.
Exploratory testing: Devise test cases on-the-fly, creating new test cases based on the results of the past test cases.
Exploratory testing is ‘the simultaneous learning, test design, and test execution’ [source: bach-et-explained] whereby the nature of the follow-up test case is decided based on the behavior of the previous test cases. In other words, running the system and trying out various operations. It is called exploratory testing because testing is driven by observations during testing. Exploratory testing usually starts with areas identified as error-prone, based on the tester’s past experience with similar systems. One tends to conduct more tests for those operations where more faults are found.
Here is an example thought process behind a segment of an exploratory testing session:
“Hmm... looks like feature x is broken. This usually means feature n and k could be broken too; you need to look at them soon. But before that, you should give a good test run to feature y because users can still use the product if feature y works, even if x doesn’t work. Now, if feature y doesn’t work 100%, you have a major problem and this has to be made known to the development team sooner rather than later...”
Exploratory testing is also known as reactive testing, error guessing technique, attack-based testing, and bug hunting.
Which approach is better – scripted or exploratory? A mix is better.
The success of exploratory testing depends on the tester’s prior experience and intuition. Exploratory testing should be done by experienced testers, using a clear strategy/plan/framework. Ad-hoc exploratory testing by unskilled or inexperienced testers without a clear strategy is not recommended for real-world non-trivial systems. While exploratory testing may allow us to detect some problems in a relatively short time, it is not prudent to use exploratory testing as the sole means of testing a critical system.
Scripted testing is more systematic, and hence, likely to discover more bugs given sufficient time, while exploratory testing would aid in quick error discovery, especially if the tester has a lot of experience in testing similar systems.
In some contexts, you will achieve your testing mission better through a more scripted approach; in other contexts, your mission will benefit more from the ability to create and improve tests as you execute them. I find that most situations benefit from a mix of scripted and exploratory approaches. --[source: bach-et-explained]
Acceptance testing (aka User Acceptance Testing (UAT): test the system to ensure it meets the user requirements.
Acceptance tests give an assurance to the customer that the system does what it is intended to do. Acceptance test cases are often defined at the beginning of the project, usually based on the use case specification. Successful completion of UAT is often a prerequisite to the project sign-off.
Acceptance testing comes after system testing. Similar to system testing, acceptance testing involves testing the whole system.
Some differences between system testing and acceptance testing:
System Testing | Acceptance Testing |
---|---|
Done against the system specification | Done against the requirements specification |
Done by testers of the project team | Done by a team that represents the customer |
Done on the development environment or a test bed | Done on the deployment site or on a close simulation of the deployment site |
Both negative and positive test cases | More focus on positive test cases |
Note: negative test cases: cases where the SUT is not expected to work normally e.g., incorrect inputs; positive test cases: cases where the SUT is expected to work normally
Requirement specification versus system specification
The requirement specification need not be the same as the system specification. Some example differences:
Requirements specification | System specification |
---|---|
limited to how the system behaves in normal working conditions | can also include details on how it will fail gracefully when pushed beyond limits, how to recover, etc. specification |
written in terms of problems that need to be solved (e.g., provide a method to locate an email quickly) | written in terms of how the system solves those problems (e.g., explain the email search feature) |
specifies the interface available for intended end-users | could contain additional APIs not available for end-users (for the use of developers/testers) |
However, in many cases one document serves as both a requirement specification and a system specification.
Passing system tests does not necessarily mean passing acceptance testing. Some examples:
An automated test case can be run programmatically and the result of the test case (pass or fail) is determined programmatically. Compared to manual testing, automated testing reduces the effort required to run tests repeatedly and increases precision of testing (because manual testing is susceptible to human errors).
A simple way to semi-automate testing of a CLI (Command Line Interface) app is by using input/output re-direction. Here are the high-level steps:
Let's assume you are testing a CLI app called AddressBook
. Here are the detailed steps:
Store the test input in the text file input.txt
.
Store the output you expect from the SUT in another text file expected.txt
.
Run the program as given below, which will redirect the text in input.txt
as the input to AddressBook
and similarly, will redirect the output of AddressBook
to a text file output.txt
. Note that this does not require any changes in AddressBook
code.
java AddressBook < input.txt > output.txt
The way to run a CLI program differs based on the language.
e.g., In Python, assuming the code is in AddressBook.py
file, use the command
python AddressBook.py < input.txt > output.txt
If you are using Windows, use a normal MS-DOS terminal (i.e., cmd.exe
) to run the app, not a PowerShell window.
Next, you compare output.txt
with the expected.txt
. This can be done using a utility such as Windows' FC
(i.e., File Compare) command, Unix's diff
command, or a GUI tool such as WinMerge.
FC output.txt expected.txt
Note that the above technique is only suitable when testing CLI apps, and only if the exact output can be predetermined. If the output varies from one run to the other (e.g., it contains a time stamp), this technique will not work. In those cases, you need more sophisticated ways of automating tests.
A test driver is the code that ‘drives’ the for the purpose of testing i.e., invoking the SUT with test inputs and verifying if the behavior is as expected.
PayrollTest
‘drives’ the Payroll
class by sending it test inputs and verifies if the output is as expected.
public class PayrollTest {
public static void main(String[] args) throws Exception {
// test setup
Payroll p = new Payroll();
// test case 1
p.setEmployees(new String[]{"E001", "E002"});
// automatically verify the response
if (p.totalSalary() != 6400) {
throw new Error("case 1 failed ");
}
// test case 2
p.setEmployees(new String[]{"E001"});
if (p.totalSalary() != 2300) {
throw new Error("case 2 failed ");
}
// more tests...
System.out.println("All tests passed");
}
}
JUnit is a tool for automated testing of Java programs. Similar tools are available for other languages and for automating different types of testing.
This is an automated test for a Payroll
class, written using JUnit libraries.
// other test methods
@Test
public void testTotalSalary() {
Payroll p = new Payroll();
// test case 1
p.setEmployees(new String[]{"E001", "E002"});
assertEquals(6400, p.totalSalary());
// test case 2
p.setEmployees(new String[]{"E001"});
assertEquals(2300, p.totalSalary());
// more tests...
}
Most modern IDEs have integrated support for testing tools. The figure below shows the JUnit output when running some JUnit tests using the Eclipse IDE.
If a software product has a GUI (Graphical User Interface) component, all product-level testing (i.e., the types of testing mentioned above) need to be done using the GUI. However, testing the GUI is much harder than testing the CLI (Command Line Interface) or API, for the following reasons:
Moving as much logic as possible out of the GUI can make GUI testing easier. That way, you can bypass the GUI to test the rest of the system using automated API testing. While this still requires the GUI to be tested, the number of such test cases can be reduced as most of the system will have been tested using automated API testing.
There are testing tools that can automate GUI testing.
Some tools used for automated GUI testing:
TestFX can do automated testing of JavaFX GUIs
Visual Studio supports the ‘record replay’ type of GUI test automation.
Selenium can be used to automate testing of web application UIs
Test coverage is a metric used to measure the extent to which testing exercises the code i.e., how much of the code is 'covered' by the tests.
Here are some examples of different coverage criteria:
if
statement evaluated to both true
and false
with separate test cases during testing is considered 'covered'. if(x > 2 && x < 44)
is considered one decision point but two conditions.
For 100% branch or decision coverage, two test cases are required:
(x > 2 && x < 44) == true
: [e.g., x == 4
](x > 2 && x < 44) == false
: [e.g., x == 100
]For 100% condition coverage, three test cases are required:
(x > 2) == true
, (x < 44) == true
: [e.g., x == 4
] [see note 1](x < 44) == false
: [e.g., x == 100
](x > 2) == false
: [e.g., x == 0
]Note 1: A case where both conditions are true
is needed because most execution environments use a short circuiting behavior for compound boolean expressions e.g., given an expression c1 && c2
, c2
will not be evaluated if c1
is false
(as the final result is going to be false
anyway).
Consider the following Java method.
void findRate(int input) {
if (input == 0) {
return 0;
}
cap = 100/input;
if (cap < 0) {
return -1;
} else {
return cap;
}
}
It has 3 paths, as follows:
2
-> 3
-> exit (can be triggered by input 0
)2
-> 5
-> 6
-> 7
-> exit (can be triggered by input -5
)2
-> 5
-> 6
-> 9
-> exit (can be triggered by input 8
)So, to achieve 100% path coverage, we need at least 3 test cases (e.g., 0
, -5
, 8
).
A loop can increase the path count greatly.
void sayHello(List<String> names) {
for (String n : names) {
System.out.println(n);
}
}
The number of paths through this method is very large, as each possible length of names
produces a unique path.
2
-> exit (if names
is empty)2
-> 3
-> exit (if names
has one entry)2
-> 3
-> 2
-> 3
-> exit (if names
has two entries)
1 ...So, achieving 100% path coverage of this method will be extremely difficult.
Measuring coverage is often done using coverage analysis tools. Most IDEs have inbuilt support for measuring test coverage, or at least have plugins that can measure test coverage.
Coverage analysis can be useful in improving the quality of testing e.g., if a set of test cases does not achieve 100% branch coverage, more test cases can be added to cover missed branches.
Measuring code coverage in IntelliJ IDEA (watch from 4 minutes 50 seconds
mark)
Dependency injection is the process of 'injecting' objects to replace current dependencies with a different object. This is often used to inject stubs to isolate the from its so that it can be tested in isolation.
A Foo
object normally depends on a Bar
object, but you can inject a BarStub
object so that the Foo
object no longer depends on a Bar
object. Now you can test the Foo
object in isolation from the Bar
object.
Test-Driven Development(TDD) advocates writing the tests before writing the SUT, while evolving functionality and tests in small increments. In TDD you first define the precise behavior of the SUT using test code, and then update the SUT to match the specified behavior. While TDD has its fair share of detractors, there are many who consider it a good way to reduce defects. One big advantage of TDD is that it guarantees the code is testable.
Except for trivial , is not practical because such testing often requires a massive/infinite number of test cases.
Consider the test cases for adding a string object to a :
Exhaustive testing of this operation can take many more test cases.
Program testing can be used to show the presence of bugs, but never to show their absence! --Edsger Dijkstra
Every test case adds to the cost of testing. In some systems, a single test case can cost thousands of dollars e.g. on-field testing of flight-control software. Therefore, test cases need to be designed to make the best use of testing resources. In particular:
Testing should be effective i.e., it finds a high percentage of existing bugs e.g., a set of test cases that finds 60 defects is more effective than a set that finds only 30 defects in the same system.
Testing should be efficient i.e., it has a high rate of success (bugs found/test cases) a set of 20 test cases that finds 8 defects is more efficient than another set of 40 test cases that finds the same 8 defects.
For testing to be , each new test you add should be targeting a potential fault that is not already targeted by existing test cases. There are test case design techniques that can help us improve the E&E of testing.
A positive test case is when the test is designed to produce an expected/valid behavior. On the other hand, a negative test case is designed to produce a behavior that indicates an invalid/unexpected situation, such as an error message.
Consider the testing of the method print(Integer i)
which prints the value of i
.
i == new Integer(50);
i == null;
Test case design can be of three types, based on how much of the SUT's internal details are considered when designing test cases:
Black-box (aka specification-based or responsibility-based) approach: test cases are designed exclusively based on the SUT’s specified external behavior.
White-box (aka glass-box or structured or implementation-based) approach: test cases are designed based on what is known about the SUT’s implementation, i.e., the code.
Gray-box approach: test case design uses some important information about the implementation. For example, if the implementation of a sort operation uses different algorithms to sort lists shorter than 1000 items and lists longer than 1000 items, more meaningful test cases can then be added to verify the correctness of both algorithms.
Consider the testing of the following operation.
isValidMonth(m)
: returns true
if m
(an int
) is in the range [1..12]
It is inefficient and impractical to test this method for all integer values [-MIN_INT to MAX_INT]
. Fortunately, there is no need to test all possible input values. For example, if the input value 233
fails to produce the correct result, the input 234
is likely to fail too; there is no need to test both.
In general, most SUTs do not treat each input in a unique way. Instead, they process all possible inputs in a small number of distinct ways. That means a range of inputs is treated the same way inside the SUT. Equivalence partitioning (EP) is a test case design technique that uses the above observation to improve the E&E of testing.
Equivalence partition (aka equivalence class): A group of test inputs that are likely to be processed by the SUT in the same way.
By dividing possible inputs into equivalence partitions you can,
Equivalence partitions (EPs) are usually derived from the specifications of the SUT.
These could be EPs for the isValidMonth example:
true
(produces false
)true
true
(produces false
)When the SUT has multiple inputs, you should identify EPs for each input.
Consider the method duplicate(String s, int n): String
which returns a String
that contains s
repeated n
times.
Example EPs for s
:
Example EPs for n
:
0
An EP may not have adjacent values.
Consider the method isPrime(int i): boolean
that returns true if i
is a prime number.
EPs for i
:
Some inputs have only a small number of possible values and a potentially unique behavior for each value. In those cases, you have to consider each value as a partition by itself.
Consider the method showStatusMessage(GameStatus s): String
that returns a unique String
for each of the possible values of s (GameStatus
is an enum
). In this case, each possible value of s
will have to be considered as a partition.
Note that the EP technique is merely a heuristic and not an exact science, especially when applied manually (as opposed to using an automated program analysis tool to derive EPs). The partitions derived depend on how one ‘speculates’ the SUT to behave internally. Applying EP under a glass-box or gray-box approach can yield more precise partitions.
Consider the EPs given above for the method isValidMonth
. A different tester might use these EPs instead:
true
false
Some more examples:
Specification | Equivalence partitions |
---|---|
| [ |
| [ |
When deciding EPs of OOP methods, you need to identify the EPs of all data participants that can potentially influence the behaviour of the method, such as,
Consider this method in the DataStack
class:
push(Object o): boolean
o
to the top of the stack if the stack is not full.true
if the push operation was a success.MutabilityException
if the global flag FREEZE==true
.InvalidValueException
if o
is null.EPs:
DataStack
object: [full] [not full]o
: [null] [not null]FREEZE
: [true][false] Consider a simple Minesweeper app. What are the EPs for the newGame()
method of the Logic
component?
As newGame()
does not have any parameters, the only obvious participant is the Logic
object itself.
Note that if the glass-box or the grey-box approach is used, other associated objects that are involved in the method might also be included as participants. For example, the Minefield
object can be considered as another participant of the newGame()
method. Here, the black-box approach is assumed.
Next, let us identify equivalence partitions for each participant. Will the newGame()
method behave differently for different Logic
objects? If yes, how will it differ? In this case, yes, it might behave differently based on the game state. Therefore, the equivalence partitions are:
PRE_GAME
: before the game starts, minefield does not exist yetREADY
: a new minefield has been created and the app is waiting for the player’s first moveIN_PLAY
: the current minefield is already in useWON
, LOST
: let us assume that newGame()
behaves the same way for these two values Consider the Logic
component of the Minesweeper application. What are the EPs for the markCellAt(int x, int y)
method? The partitions in bold represent valid inputs.
Logic
: PRE_GAME, READY, IN_PLAY, WON, LOSTx
: [MIN_INT..-1] [0..(W-1)] [W..MAX_INT] (assuming a minefield size of WxH)y
: [MIN_INT..-1] [0..(H-1)] [H..MAX_INT]Cell
at (x,y)
: HIDDEN, MARKED, CLEAREDBoundary Value Analysis (BVA) is a test case design heuristic that is based on the observation that bugs often result from incorrect handling of boundaries of equivalence partitions. This is not surprising, as the end points of boundaries are often used in branching instructions, etc., where the programmer can make mistakes.
The markCellAt(int x, int y)
operation could contain code such as if (x > 0 && x <= (W-1))
which involves the boundaries of x’s equivalence partitions.
BVA suggests that when picking test inputs from an equivalence partition, values near boundaries (i.e., boundary values) are more likely to find bugs.
Boundary values are sometimes called corner cases.
Typically, you should choose three values around the boundary to test: one value from the boundary, one value just below the boundary, and one value just above the boundary. The number of values to pick depends on other factors, such as the cost of each test case.
Some examples:
Equivalence partition | Some possible test values (boundaries are in bold) |
---|---|
[1-12] | 0,1,2, 11,12,13 |
[MIN_INT, 0] | MIN_INT, MIN_INT+1, -1, 0 , 1 |
[any non-null String] | Empty String, a String of maximum possible length |
[prime numbers] | No specific boundary |
[non-empty Stack] | Stack with: no elements, one element, two elements, no empty spaces, only one empty space |
An SUT can take multiple inputs. You can select values for each input (using equivalence partitioning, boundary value analysis, or some other technique).
An SUT that takes multiple inputs and some values chosen for each input:
calculateGrade(participation, projectGrade, isAbsent, examScore)
Input | Valid values to test | Invalid values to test |
---|---|---|
participation | 0, 1, 19, 20 | 21, 22 |
projectGrade | A, B, C, D, F | |
isAbsent | true, false | |
examScore | 0, 1, 69, 70, | 71, 72 |
Testing all possible combinations is effective but not efficient. If you test all possible combinations for the above example, you need to test 6x5x2x6=360 cases. Doing so has a higher chance of discovering bugs (i.e., effective) but the number of test cases will be too high (i.e., not efficient). Therefore, you need smarter ways to combine test inputs that are both effective and efficient.
Given below are some basic strategies for generating a set of test cases by combining multiple test inputs.
Let's assume the SUT has the following three inputs and you have selected the given values for testing:
SUT: foo(char p1, int p2, boolean p3)
Values to test:
Input | Values |
---|---|
p1 | a, b, c |
p2 | 1, 2, 3 |
p3 | T, F |
The all combinations strategy generates test cases for each unique combination of test inputs.
This strategy generates 3x3x2=18 test cases.
Test Case | p1 | p2 | p3 |
---|---|---|---|
1 | a | 1 | T |
2 | a | 1 | F |
3 | a | 2 | T |
... | ... | ... | ... |
18 | c | 3 | F |
The at least once strategy includes each test input at least once.
This strategy generates 3 test cases.
Test Case | p1 | p2 | p3 |
---|---|---|---|
1 | a | 1 | T |
2 | b | 2 | F |
3 | c | 3 | VV/IV |
VV/IV = Any Valid Value / Any Invalid Value
The all pairs strategy creates test cases so that for any given pair of inputs, all combinations between them are tested. It is based on the observation that a bug is rarely the result of more than two interacting factors. The resulting number of test cases is lower than the all combinations strategy, but higher than the at least once approach.
This strategy generates 9 test cases:
Test Case | p1 | p2 | p3 |
---|---|---|---|
1 | a | 1 | T |
2 | a | 2 | T |
3 | a | 3 | F |
4 | b | 1 | F |
5 | b | 2 | T |
6 | b | 3 | F |
7 | c | 1 | T |
8 | c | 2 | F |
9 | c | 3 | T |
A variation of this strategy is to test all pairs of inputs but only for inputs that could influence each other.
Testing all pairs between p1 and p3 only while ensuring all p2 values are tested at least once:
Test Case | p1 | p2 | p3 |
---|---|---|---|
1 | a | 1 | T |
2 | a | 2 | F |
3 | b | 3 | T |
4 | b | VV/IV | F |
5 | c | VV/IV | T |
6 | c | VV/IV | F |
The random strategy generates test cases using one of the other strategies and then picks a subset randomly (presumably because the original set of test cases is too big).
There are other strategies that can be used too.
Consider the following scenario.
SUT: printLabel(String fruitName, int unitPrice)
Selected values for fruitName
(invalid values are underlined):
Values | Explanation |
---|---|
Apple | Label format is round |
Banana | Label format is oval |
Cherry | Label format is square |
Dog | Not a valid fruit |
Selected values for unitPrice
:
Values | Explanation |
---|---|
1 | Only one digit |
20 | Two digits |
0 | Invalid because 0 is not a valid price |
-1 | Invalid because negative prices are not allowed |
Suppose these are the test cases being considered.
Case | fruitName | unitPrice | Expected |
---|---|---|---|
1 | Apple | 1 | Print round label |
2 | Banana | 20 | Print oval label |
3 | Cherry | 0 | Error message “invalid price” |
4 | Dog | -1 | Error message “invalid fruit" |
It looks like the test cases were created using the at least once strategy. After running these tests, can you confirm that the square-format label printing is done correctly?
Cherry
-- the only input that can produce a square-format label -- is in a negative test case which produces an error message instead of a label. If there is a bug in the code that prints labels in square-format, these tests cases will not trigger that bug.In this case, a useful heuristic to apply is each valid input must appear at least once in a positive test case. Cherry
is a valid test input and you must ensure that it appears at least once in a positive test case. Here are the updated test cases after applying that heuristic.
Case | fruitName | unitPrice | Expected |
---|---|---|---|
1 | Apple | 1 | Print round label |
2 | Banana | 20 | Print oval label |
2.1 | Cherry | VV | Print square label |
3 | VV | 0 | Error message “invalid price” |
4 | Dog | -1 | Error message “invalid fruit" |
VV/IV = Any Invalid or Valid Value VV = Any Valid Value
To verify the SUT is handling a certain invalid input correctly, it is better to test that invalid input without combining it with other invalid inputs. For example, consider the test case 4 of test cases designed in [Heuristic: each valid input at least once in a positive test case]. After running that test case, can you be sure that the error message “invalid fruit” is caused by the invalid fruitName Dog
?
-1
in that test case, due to a bug in the code.Therefore, if that test case was intended to verify that the invalid fruitName Dog
triggers the "invalid fruit" error message, it is better not to include the invalid unitPrice -1
in that test case at the same time. If the invalid value -1
needs to be tested, we should test it in a separate test case.
After applying the above insight to our running example, you get the following test cases.
Case | fruitName | unitPrice | Expected |
---|---|---|---|
1 | Apple | 1 | Print round label |
2 | Banana | 20 | Print oval label |
2.1 | Cherry | VV | Print square label |
3 | VV | 0 | Error message “invalid price” |
4 | VV | -1 | Error message “invalid price" |
4.1 | Dog | VV | Error message “invalid fruit" |
VV/IV = Any Invalid or Valid Value VV = Any Valid Value
This is not to say never have more than one invalid input in a test case. In fact, an SUT might work correctly when only one invalid input is given but not when a certain combination of multiple invalid inputs is given. Hence, it is still useful to have test cases with multiple invalid inputs, after you already have confirmed that the SUT works when only one invalid input is given.
Test invalid inputs individually before combining them is the heuristic we learned here. As a test case with multiple invalid inputs by itself does not confirm that the SUT works for each of those invalid inputs, you are better off testing the SUT with one-invalid-input-at-a-time first, and if you can afford more test cases, also testing with combinations of invalid inputs.
Consider the calculateGrade scenario given below:
calculateGrade(participation, projectGrade, isAbsent, examScore)
To get the first cut of test cases, let’s apply the at least once strategy.
Test cases for calculateGrade V1
Case No. | participation | projectGrade | isAbsent | examScore | Expected |
---|---|---|---|---|---|
1 | 0 | A | true | 0 | ... |
2 | 1 | B | false | 1 | ... |
3 | 19 | C | VV/IV | 69 | ... |
4 | 20 | D | VV/IV | 70 | ... |
5 | 21 | F | VV/IV | 71 | Err Msg |
6 | 22 | VV/IV | VV/IV | 72 | Err Msg |
VV/IV = Any Valid or Invalid Value, Err Msg = Error Message
Next, let’s apply the each valid input at least once in a positive test case heuristic. Test case 5 has a valid value for projectGrade=F
that doesn't appear in any other positive test case. Let's replace test case 5 with 5.1 and 5.2 to rectify that.
Test cases for calculateGrade V2
Case No. | participation | projectGrade | isAbsent | examScore | Expected |
---|---|---|---|---|---|
1 | 0 | A | true | 0 | ... |
2 | 1 | B | false | 1 | ... |
3 | 19 | C | VV | 69 | ... |
4 | 20 | D | VV | 70 | ... |
5.1 | VV | F | VV | VV | ... |
5.2 | 21 | VV/IV | VV/IV | 71 | Err Msg |
6 | 22 | VV/IV | VV/IV | 72 | Err Msg |
VV = Any Valid Value VV/IV = Any Valid or Invalid Value
Next, you have to apply the no more than one invalid input in a test case heuristic. Test cases 5.2 and 6 don't follow that heuristic. Let's rectify the situation as follows:
Test cases for calculateGrade V3
Case No. | participation | projectGrade | isAbsent | examScore | Expected |
---|---|---|---|---|---|
1 | 0 | A | true | 0 | ... |
2 | 1 | B | false | 1 | ... |
3 | 19 | C | VV | 69 | ... |
4 | 20 | D | VV | 70 | ... |
5.1 | VV | F | VV | VV | ... |
5.2 | 21 | VV | VV | VV | Err Msg |
5.3 | 22 | VV | VV | VV | Err Msg |
6.1 | VV | VV | VV | 71 | Err Msg |
6.2 | VV | VV | VV | 72 | Err Msg |
Next, you can assume that there is a dependency between the inputs examScore
and isAbsent
such that an absent student can only have examScore=0
. To cater for the hidden invalid case arising from this, you can add a new test case where isAbsent=true
and examScore!=0
. In addition, test cases 3-6.2 should have isAbsent=false
so that the input remains valid.
Test cases for calculateGrade V4
Case No. | participation | projectGrade | isAbsent | examScore | Expected |
---|---|---|---|---|---|
1 | 0 | A | true | 0 | ... |
2 | 1 | B | false | 1 | ... |
3 | 19 | C | false | 69 | ... |
4 | 20 | D | false | 70 | ... |
5.1 | VV | F | false | VV | ... |
5.2 | 21 | VV | false | VV | Err Msg |
5.3 | 22 | VV | false | VV | Err Msg |
6.1 | VV | VV | false | 71 | Err Msg |
6.2 | VV | VV | false | 72 | Err Msg |
7 | VV | VV | true | !=0 | Err Msg |
Use cases can be used for system testing and acceptance testing. For example, the main success scenario can be one test case while each variation (due to extensions) can form another test case. However, note that use cases do not specify the exact data entered into the system. Instead, it might say something like user enters his personal data into the system
. Therefore, the tester has to choose data by considering equivalence partitions and boundary values. The combinations of these could result in one use case producing many test cases.
To increase the E&E of testing, high-priority use cases are given more attention. For example, a scripted approach can be used to test high-priority test cases, while an exploratory approach is used to test other areas of concern that could emerge during testing.
Before learning about Git, let us first understand what revision control is.
Given below is a general introduction to revision control, adapted from bryan-mercurial-guide:
Revision control is the process of managing multiple versions of a piece of information. In its simplest form, this is something that many people do by hand: every time you modify a file, save it under a new name that contains a number, each one higher than the number of the preceding version.
Manually managing multiple versions of even a single file is an error-prone task, though, so software tools to help automate this process have long been available. The earliest automated revision control tools were intended to help a single user to manage revisions of a single file. Over the past few decades, the scope of revision control tools has expanded greatly; they now manage multiple files, and help multiple people to work together. The best modern revision control tools have no problem coping with thousands of people working together on projects that consist of hundreds of thousands of files.
There are a number of reasons why you or your team might want to use an automated revision control tool for a project.
Most of these reasons are equally valid, at least in theory, whether you're working on a project by yourself, or with a hundred other people.
A revision is the state of a piece of information at a specific point in time, resulting from changes made to it e.g., if you modify the code and save the file, you have a new revision (or a new version) of that file. Some seem to use this term interchangeably with version while others seem to distinguish the two -- here, let us treat them as the same, for simplicity.
Revision Control Software (RCS) are the software tools that automate the process of Revision Control i.e., managing revisions of software . RCS are also known as Version Control Software (VCS), and by a few other names.
Git is the most widely used RCS today. Other RCS tools include Mercurial, Subversion (SVN), Perforce, CVS (Concurrent Versions System), Bazaar, TFS (Team Foundation Server), and Clearcase.
Github is a web-based project hosting platform for projects using Git for revision control. Other similar services include GitLab, BitBucket, and SourceForge.
To be able to save snapshots of a folder using Git, you must first put the folder under Git's control by initialising a Git repository in that folder.
Normally, we use Git to manage a revision history of a specific folder, which gives us the ability to revision-control any file in that folder and its subfolders.
To put a folder under the control of Git, we initialise a repository (short name: repo) in that folder. This way, we can initialise repos in different folders, to revision-control different clusters of files independently of each other e.g., files belonging to different projects.
You can follow the hands-on practical below to learn how to initialise a repo in a folder.
What is this? HANDS-ON panels contain hands-on activities you can do as you learn Git. If you are new to Git, we strongly recommend that you do them yourself (even if they appear straightforward), as hands-on usage will help you internalise the concepts and operations better.
1 First, choose a folder. The folder may or may not have any files in it already. For this practical, let us create a folder named things
for this purpose.
cd my-projects
mkdir things
2 Then cd
into it.
cd things
3 Run the git status
command to check the status of the folder.
git status
fatal: not a git repository (or any of the parent directories): .git
Don't panic. The error message is expected. It confirms that the folder currently does not have a Git repo.
4 Now, initialise a repository in that folder.
Use the command git init
which should initialise the repo.
git init
Initialized empty Git repository in things/.git/
The output might also contain a hint about a name for an initial branch (e.g., hint: Using 'master' as the name for the initial branch ...
). You can ignore that for now.
Note how the output mentions the repo being created in things/.git/
(not things/
). More on that later.
Windows: Click File
→ Clone/New…
→ Click on + Create
button on the top menu bar.
Enter the location of the directory and click Create
.
Mac: New...
→ Create Local Repository
(or Create New Repository
) → Click ...
button to select the folder location for the repository → click the Create
button.
done!
Initialising a repo results in two things:
To confirm, you can run the git status
command. It should respond with something like the following:
git status
On branch master
No commits yet
nothing to commit (create/copy files and use "git add" to track)
Don't worry if you don't understand the output (we will learn about them later); what matters is that it no longer gives an error message as it did before.
done!
.git
inside the things
folder. This folder will be used by Git to store metadata about this repository.A Git-controlled folder is divided into two main parts:
.git
subfolder, which contains all the metadata and history.To save a snapshot, you start by specifying what to include in it, also called staging.
Git considers new files that you add to the working directory as 'untracked' i.e., Git is aware of them, but they are not yet under Git's control. The same applies to files that existed in the working folder at the time you initialised the repo.
A Git repo has an internal space called the staging area which it uses to build the next snapshot. Another name for the staging area is the index.
We can stage an untracked file to tell Git that we want its current version to be included in the next snapshot. Once you stage an untracked file, it becomes 'tracked' (i.e., under Git's control). A staged file can be unstaged to indicate that we no longer want it to be included in the next snapshot.
In the example below, you can see how staging files change the status of the repo as you go from (a) to (c).
staging area
[empty]
other metadata ...
├─ fruits.txt (untracked!)
└─ colours.txt (untracked!)
staging area
└─ fruits.txt
other metadata ...
├─ fruits.txt (tracked)
└─ colours.txt (untracked!)
fruits.txt
.staging area
├─ fruits.txt
└─ colours.txt
other metadata ...
├─ fruits.txt (tracked)
└─ colours.txt (tracked)
colours.txt
.1 First, add a file (e.g., fruits.txt
) to the things
folder.
Here is an easy way to do that with a single terminal command.
echo -e "apples\nbananas\ncherries" > fruits.txt
apples
bananas
cherries
Windows users: Use the git-bash terminal to run the above command (and all commands given in these lessons). Some of them might not work in other terminals such as the PowerShell.
To see the content of the file, you can use the cat
command:
cat fruits.txt
2 Stage the new file.
2.1 Check the status of the folder using the git status
command.
git status
On branch master
No commits yet
Untracked files:
(use "git add <file>..." to include in what will be committed)
fruits.txt
nothing added to commit but untracked files present (use "git add" to track)
2.2 Use the git add <file>
command to stage the file.
git add fruits.txt
You can replace the add
with stage
(e.g., git stage fruits.txt
) and the result is the same (they are synonyms).
Windows users: When using the echo
command to write to text files from Git Bash, you might see a warning LF will be replaced by CRLF the next time Git touches it
when Git interacts with such a file. This warning is caused by the way line endings are handled differently by Git and Windows. You can simply ignore it, or suppress it in future by running the following command:
git config --global core.safecrlf false
2.3 Check the status again. You can see the file is no longer 'untracked'.
git status
On branch master
No commits yet
Changes to be committed:
(use "git rm --cached <file>..." to unstage)
new file: fruits.txt
As before, don't worry if you don't understand the content of the output (we'll unpack it in a later lesson). The point to note is that the file is no longer listed as 'untracked'.
2.1 Note how the file is shown as ‘unstaged’. The question mark icon indicates the file is untracked.
If the newly-added file does not show up in Sourcetree UI, refresh the UI (: F5
| ⌥+R)
Sourcetree screenshots/instructions: vs
Note that Sourcetree UI can vary slightly between Windows and Mac versions. Some of the screenshots given in our lessons are from the Windows version while some are from the Mac version.
In som cases, we have specified how they differ.
In other cases, you may need to adapt if the given screenshots/instructions are slightly different from what you are seeing in your Sourcetree.
2.2 Stage the file:
Select the fruits.txt
and click on the Stage Selected
button.
Staging can be done using tick boxes or the ...
menu in front of the file.
2.3 Note how the file is staged now i.e., fruits.txt
appears in the Staged files
panel now.
If Sourcetree shows a \ No newline at the end of the file
message below the staged lines (i.e., below the cherries
line in the above screenshot), that is because you did not hit enter after entering the last line of the file (hence, Git is not sure if that line is complete). To rectify, move the cursor to the end of the last line in that file and hit enter (like you are adding a blank line below it). This new change will now appear as an 'unstaged' change. Stage it as well.
done!
If you modify a staged file, it goes into the 'modified' state i.e., the file contains modifications that are not present in the copy that is waiting (in the staging area) to be included in the next snapshot. If you wish to include these new changes in the next snapshot, you need to stage the file again, which will overwrite the copy of the file that was previously in the staging area.
The example below shows how the status of a file changes when it is modified after it was staged.
staging area
Alice
other metadata ...
Alice
staging area
Alice
other metadata ...
Alice
Bob
staging area
Alice
Bob
other metadata ...
Alice
Bob
1 First, add another line to fruits.txt
, to make it 'modified'.
Here is a way to do that with a single terminal command.
echo "dragon fruits" >> fruits.txt
apples
bananas
cherries
dragon fruits
2 Now, verify that Git sees that file as 'modified'.
Use the git status
command to check the status of the working directory.
$ git status
On branch master
No commits yet
Changes to be committed:
(use "git rm --cached <file>..." to unstage)
new file: fruits.txt
Changes not staged for commit:
(use "git add <file>..." to update what will be committed)
(use "git restore <file>..." to discard changes in working directory)
modified: fruits.txt
Note how fruits.txt
now appears twice, once as new file: ...
(representing the version of the file we staged earlier, which had only three lines) and once as modified: ...
(representing the latest version of the file which now has a fourth line).
Note how fruits.txt
appears in the Staged files
panel as well as 'Unstaged files'.
3 Stage the file again, the same way you added/staged it earlier.
4 Verify that Git no longer sees it as 'modified', similar to step 2.
done!
Staging applies regardless of whether a file is currently tracked.
Git also supports fine-grained selective staging i.e., staging only specific changes within a file while leaving other changes to the same file unstaged. This will be covered in a later lesson.
Git does not track empty folders. It tracks only folders that contain tracked files.
You can test this by adding an empty subfolder inside the things
folder (e.g., things/more-things
) and checking if it shows up as 'untracked' (it will not). If you add a file to that folder (e.g., things/more-things/food.txt
) and then staged that file (e.g., git add more-things/food.txt
), the folder will now be included in the next snapshot.
PRO-TIP: Applying a Git command to multiple files in one go
When a Git command expects a list of files or paths as a parameter (as the git add
command does), these parameters are known as pathspecs — patterns that tell Git which files or directories to operate on. Pathspecs can be simple file names, directory names, or more complex patterns.
Here are some common ways to write them, shown with examples using the git add <pathspec>
command:
Specify multiple files, separated by spaces:
git add f1.txt f2.txt data/lists/f3.txt # stages the specified three files
Use a glob pattern:
git add '*.txt' # stages all .txt files in the current directory
Quoting the glob pattern is recommended so your shell doesn’t expand it before Git sees it.
Use .
to indicate 'all in the current directory and subdirectories':
git add . # stages all files in current directory and its subdirectories
Specific directory, to indicate 'this directory and its subdirectories':
git add path/to/dir # stages all files in path/to/dir and its subdirectories
Negated pathspecs, to indicate 'except these':
git add . ':!*.log' # stage everything except .log files
Git supports combining these features — for example, you could add all .txt
files except those in a certain folder using:
git add '*.txt' ':!docs/*.txt'
After staging, you can now proceed to save the snapshot, aka creating a commit.
Saving a snapshot is called committing and a saved snapshot is called a commit.
A Git commit is a full snapshot of your working directory based on the files you have staged, more precisely, a record of the exact state of all files in the staging area (index) at that moment -- even the files that have not changed since the last commit. This is in contrast to other revision control software that only store the in a commit. Consequently, a Git commit has all the information it needs to recreate the snapshot of the working directory at the time the commit was created.
A commit also includes metadata such as the author, date, and an optional commit message describing the change.
A Git commit is a snapshot of all tracked files, not simply a delta of what changed since the last commit.
Assuming you have previously staged changes to the fruits.txt
, go ahead and create a commit.
1 First, let us do a sanity check using the git status
command.
git status
On branch master
No commits yet
Changes to be committed:
(use "git rm --cached <file>..." to unstage)
new file: fruits.txt
2 Now, create a commit using the commit
command. The -m
switch is used to specify the commit message.
git commit -m "Add fruits.txt"
[master (root-commit) d5f91de] Add fruits.txt
1 file changed, 5 insertions(+)
create mode 100644 fruits.txt
3 Verify the staging area is empty using the git status
command again.
git status
On branch master
nothing to commit, working tree clean
Note how the output says nothing to commit
which means the staging area is now empty.
Click the Commit
button, enter a commit message (e.g. add fruits.txt
) into the text box, and click Commit
.
done!
It is useful to be able to visualise the commits timeline, aka the revision graph.
Git commits form a timeline, as each corresponds to a point in time when you asked Git to take a snapshot of your working directory. Each commit links to at least one previous commit, forming a structure that we can traverse.
A timeline of commits is called a branch. By default, Git names the initial branch master
-- though many now use main
instead. You'll learn more about branches in future lessons. For now, just be aware that the commits you create in a new repo will be on a branch called master
(or main
) by default.
gitGraph %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master (or main)'}} }%% commit id: "Add fruits.txt" commit id: "Update fruits.txt" commit id: "Add colours.txt" commit id: "..."
Git can show you the list of commits in the Git history.
Preparation Use the things
repo you created in a previous lesson. Alternatively, you can use the commands given below to create such a repo from scratch.
mkdir things # create a folder for the repo
cd things
git init
echo -e "apples\nbananas\ncherries" > fruits.txt
git add fruits.txt
git commit -m "Add fruits.txt"
You can copy-paste a list of commands (such as commands given above), including any comments, to the terminal. After that, hit enter to run them in sequence.
1 View the list of commits, which should show just the one commit you created just now.
You can use the git log
command to see the commit history.
git log
commit ... (HEAD -> master)
Author: ... <...@...>
Date: ...
Add fruits.txt
Use the Q key to exit the output screen of the git log
command.
Note how the output has some details about the commit you just created. You can ignore most of it for now, but notice it also shows the commit message you provided.
Expand the BRANCHES
menu and click on the master
to view the history graph, which contains only one node at the moment, representing the commit you just added. For now, ignore the label master
attached to the commit.
2 Create a few more commits (i.e., a few rounds of add/edit files → stage → commit), and observe how the list of commits grows.
Here is an example list of bash commands to add two commits while observing the list of commits
echo "figs" >> fruits.txt # add another line to fruits.txt
git add fruits.txt # stage the updated file
git commit -m "Insert figs into fruits.txt" # commit the changes
git log # check commits list
echo "a file for colours" >> colours.txt # add a colours.txt file
echo "a file for shapes" >> shapes.txt # add a shapes.txt file
git add colours.txt shapes.txt # stage both files in one go
git commit -m "Add colours.txt, shapes.txt" # commit the changes
git log # check commits list
The output of the final git log
should be something like this:
commit ... (HEAD -> master)
Author: ... <...@...>
Date: ...
Add colours.txt, shapes.txt
commit ...
Author: ... <...@...>
Date: ...
Insert figs into fruits.txt
commit ...
Author: ... <...@...>
Date: ...
Add fruits.txt
SIDEBAR: Working with the 'less' pager
Some Git commands — such as git log
— may show their output through a pager. A pager is a program that lets you view long text one screen at a time, so you don’t miss anything that scrolls off the top. For example, the output of git log
command will temporarily hide the current content of the terminal, and enter the pager view that shows output one screen at a time. When you exit the pager, the git log
output will disappear from view, and the previous content of the terminal will reappear.
command 1
output 1
git log
→
commit f761ea63738a...
Author: ... <...@...>
Date: Sat ...
Add colours.txt
By default, Git uses a pager called less. Given below are some useful commands you can use inside the less pager.
Command | Description |
---|---|
q | Quit less and return to the terminal |
↓ or j | Move down one line |
↑ or k | Move up one line |
Space | Move down one screen |
b | Move up one screen |
G | Go to the end of the content |
g | Go to the beginning of the content |
/pattern | Search forward for pattern (e.g., /fix ) |
n | Repeat the last search (forward) |
N | Repeat the last search (backward) |
h | Show help screen with all less commands |
If you’d rather see the output directly, without using a pager, you can add the --no-pager
flag to the command e.g.,
git --no-pager log
It is possible to ask Git to not use less at all, use a different pager, or fine-tune how less is used. For example, you can reduce Git's use of the pager (recommended), using the following command:
git config --global core.pager "less -FRX"
Explanation:
-F
: Quit if the output fits on one screen (don’t show pager unnecessarily)-R
: Show raw control characters (for coloured Git output)-X
: Keep content visible after quitting the pager (so output stays on the terminal)To see the list of commits, click on the History
item (listed under the WORKSPACE
section) on the menu on the right edge of Sourcetree.
After adding two more commits, the list of commits should look something like this:
done!
The Git data model consists of two types of entities: objects and refs (short for references). In this lesson, you will encounter examples of both.
A Git revision graph is a visualisation of a repo's revision history, consisting of one or more branches. First, let us learn to work with simpler revision graphs consisting of one branch, such as the one given below.
f761ea63738a67258628e9e54095b88ea67d95e2
) that acts like a fingerprint, ensuring that every commit can be referenced unambiguously. That is, every commit has a unique SHA-1 hash value.Given every commit has a unique hash, the commit hash values you see in our examples will be different from the hash values of your own commits, for example, when following our hands-on practicals.
Edges in the revision graph represent links between a commit and its parent commit(s). In some revision graph visualisations, you might see arrows (instead of lines) showing how each commit points to its parent commit.
Git uses refs to name and keep track of various points in a repository’s history. These refs are essentially 'named-pointers' that can serve as bookmarks to reach a certain point in the revision graph using the ref name.
In the revision graph above, there are two refs master and ←HEAD.
C3
.master
branch.HEAD
may point directly to a specific commit instead of a branch. This situation is called a "detached HEAD
", which will be covered in a later lesson.Target Use Git features to examine the revision graph of a simple repo.
Preparation Use a repo with just a few commits and only one branch.
1 First, use a simple git log
to view the list of commits.
git log
commit f761ea63738a... (HEAD -> master)
Author: ... <...@...>
Date: Sat ...
Add colours.txt, shapes.txt
commit 2bedace69990...
Author: ... <...@...>
Date: Sat ...
Add figs to fruits.txt
commit d5f91de5f0b5...
Author: ... <...@...>
Date: Fri ...
Add fruits.txt
Given below the visual representation of the same revision graph. As you can see, the log
output shows the refs slightly differently, but it is not hard to see what they mean.
2 Use the --oneline
flag to get a more concise view. Note how the commit SHA has been truncated to first seven characters (first seven characters of a commit SHA is enough for Git to identify a commit).
git log --oneline
f761ea6 (HEAD -> master, origin/master) Add colours.txt, shapes.txt
2bedace Add figs to fruits.txt
d5f91de Add fruits.txt
3 The --graph
flag makes the result closer to a graphical revision graph. Note the *
that indicates a node in a revision graph.
git log --oneline --graph
* f761ea6 (HEAD -> master, origin/master) Add colours.txt, shapes.txt
* 2bedace Add figs to fruits.txt
* d5f91de Add fruits.txt
The --graph
option is more useful when examining a more complicated revision graph consisting of multiple parallel branches.
Click the History
to see the revision graph.
HEAD
ref may not be shown -- it is implied that the HEAD
ref is pointing to the same commit the currently active branch ref is pointing.done!
To back up your Git repo on the cloud, you’ll need to use a remote repository service, such as GitHub.
A repo you have on your computer is called a local repo. A remote repo is a repo hosted on a remote computer and allows remote access. Some use cases for remote repositories:
It is possible to set up a Git remote repo on your own server, but an easier option is to use a remote repo hosting service such as GitHub.
The first step of backing up a local repo on GitHub: create an empty repository on GitHub.
You can create a remote repository based on an existing local repository, to serve as a remote copy of your local repo. For example, suppose you created a local repo and worked with it for a while, but now you want to upload it onto GitHub. The first step is to create an empty repository on GitHub.
1 Login to your GitHub account and choose to create a new repo.
2 In the next screen, provide a name for your repo. Refer the screenshot below on some guidance on how to provide the required information.
Click Create repository button to create the new repository.
If you enable any of the three Add _____
options shown above, GitHub will not only create a repo, but will also initialise it with some initial content. That is not what we want here. To create an empty remote repo, keep those options disabled.
3 Note the URL of the repo. It will be of the form
https://github.com/{your_user_name}/{repo_name}.git
.
e.g., https://github.com/johndoe/foobar.git
(note the .git
at the end)
done!
The second step of backing up a local repo on GitHub: link the local repo with the remote repo on GitHub.
A Git remote is a reference to a repository hosted elsewhere, usually on a server like GitHub, GitLab, or Bitbucket. It allows your local Git repo to communicate with another remote copy — for example, to upload locally-created commits that are missing in the remote copy.
By adding a remote, you are informing the local repo details of a remote repo it can communicate with, for example, where the repo exists and what name to use to refer to the remote.
The URL you use to connect to a remote repo depends on the protocol — HTTPS or SSH:
https://github.com/
(for GitHub users). e.g.,https://github.com/username/repo-name.git
git@github.com:
. e.g.,git@github.com:username/repo-name.git
A Git repo can have multiple remotes. You simply need to specify different names for each remote (e.g., upstream
, central
, production
, other-backup
...).
Add the empty remote repo you created on GitHub as a remote of a local repo you have.
1 In a terminal, navigate to the folder containing the local repo things
you created earlier.
2 List the current list of remotes using the git remote -v
command, for a sanity check. No output is expected if there are no remotes yet.
3 Add a new remote repo using the git remote add <remote-name> <remote-url>
command.
i.e., if using HTTPS, git remote add origin https://github.com/{YOUR-GITHUB-USERNAME}/things.git
git remote add origin https://github.com/JohnDoe/things.git # using HTTPS
git remote add origin git@github.com:JohnDoe/things.git # using SSH
4 List the remotes again to verify the new remote was added.
git remote -v
origin https://github.com/johndoe/things.git (fetch)
origin https://github.com/johndoe/things.git (push)
The same remote will be listed twice, to show that you can do two operations (fetch
and push
) using this remote. You can ignore that for now. The important thing is the remote you added is being listed.
1 Open the local repo in Sourcetree.
2 Open the dialog for adding a remote, as follows:
Choose Repository
→ Repository Settings
menu option.
Choose Repository
→ Repository Settings...
→ Choose Remotes
tab.
3 Add a new remote to the repo with the following values.
Remote name
: the name you want to assign to the remote repo i.e., origin
URL/path
: the URL of your remote repohttps://github.com/{YOUR-GITHUB-USERNAME}/things.git
Username
: your GitHub username4 Verify the remote was added by going to Repository
→ Repository Settings
again.
5 Add another remote, to verify that a repo can have multiple remotes. You can use any name (e.g., backup
and any URL for this).
done!
The third step of backing up a local repo on GitHub: push a copy of the local repo to the remote repo.
You can push content of one repository to another, usually from your local repo to a remote repo. Pushing transfers recorded Git history (such as past commits), but it does not transfer unstaged changes or untracked files.
You can configure Git to track a pairing between a local branch and a remote branch, so in future you can push from the same local branch to the corresponding remote branch without needing to specify them again. For example, you can set your local master
branch to track the master
branch on the remote repo origin
i.e., local master
branch will track the branch origin/master
.
In the revision graph above, you see a new type of ref ( origin/master). This is a remote-tracking branch ref that represents the state of a corresponding branch in a remote repository (if you previously set up the branch to 'track' a remote branch). In this example, the master
branch in the remote origin
is also at the commit C3
(which means you have not created new commits after you pushed to the remote).
If you now create a new commit C4
, the state of the revision graph will be as follows:
Explanation: When you create C4
, the current branch master
moves to C4
, and HEAD
moves along with it. However, the master
branch in the remote origin
remains at C3
(because you have not pushed C4
yet). That is, the remote-tracking branch origin/master
is one commit behind the local branch master
(or, the local branch is one commit ahead). The origin/master
ref will move to C4
only after you push your local branch to the remote again.
Preparation Use a local repo that is connected to an empty remote repo e.g., the things
repo from previous hands-on practicals:
1 Push the master
branch to the remote. Also instruct Git to track this branch pair.
Use the git push -u <remote-repo-name> <local-branch-name>
to push the commits to a remote repository.
git push -u origin master
Explanation:
push
: the Git sub-command that pushes the current local repo content to a remote repoorigin
: name of the remotemaster
: branch to push-u
(or --set-upstream
): the flag that tells Git to track that this local master
is tracking origin/master
branchClick the Push
button on the buttons ribbon at the top.
In the next dialog, ensure the settings are as follows, ensure the Track
option is selected, and click the Push
button on the dialog.
2 Observe the remote-tracking branch origin/master
is now pointing at the same commit as the master
branch.
Use the git log --oneline --graph
to see the revision graph.
* f761ea6 (HEAD -> master, origin/master) Add colours.txt, shapes.txt
* 2bedace Add figs to fruits.txt
* d5f91de Add fruits.txt
Click the History
to see the revision graph.
HEAD
ref may not be shown -- it is implied that the HEAD
ref is pointing to the same commit the currently active branch ref is pointing.origin/master
) is not showing up, you may need to enable the Show Remote Branches
option.done!
The push command can be used repeatedly to send further updates to another repo e.g., to update the remote with commits you created since you pushed the first time.
Target Add a few more commits to the same local repo, and push those commits to the remote repo.
1 Commit some changes in your local repo.
Use the git commit
command to create commits, as you did before.
Optionally, you can run the git status
command, which should confirm that your local branch is 'ahead' by one commit (i.e., the local branch has commits that are not present in the corresponding branch in the remote repo).
git status
On branch master
Your branch is ahead of 'origin/master' by 1 commit.
(use "git push" to publish your local commits)
nothing to commit, working tree clean
You can also use the git log --oneline --graph
command to see where the branch refs are. Note how the remote-tracking branch origin/master
is one commit behind the local master
.
e60deae (HEAD -> master) Update fruits list
f761ea6 (origin/master) Add colours.txt, shapes.txt
2bedace Add figs to fruits.txt
d5f91de Add fruits.txt
Create commits as you did before.
Before pushing the new commit, Sourcetree will indicate that your local branch is 'ahead' by one commit (i.e., the local branch has one new commit that is not in the corresponding branch in the remote repo).
2 Push the new commits to your fork on GitHub.
To push the newer commit(s) to the remote, any of the following commands should work:
git push origin master
git push origin
master
branch)git push
origin
and to the branch master
i.e., origin/master
)After pushing, the revision graph should look something like the following (note how both local and remote-tracking branch refs are pointing to the same commit again).
e60deae (HEAD -> master, origin/master) Update fruits list
f761ea6 Add colours.txt, shapes.txt
2bedace Add figs to fruits.txt
d5f91de Add fruits.txt
To push, click the Push
button on the top buttons ribbon, ensure the settings are as follows in the next dialog, and click the Push
button on the dialog.
After pushing the new commit to the remote, the remote-tracking branch ref should move to the new commit:
done!
Note that you can push between two repos only if those repos have a shared history among them (i.e., one should have been created by copying the other).
Git allows you to specify which files should be omitted from revision control.
You can specify which files Git should ignore from revision control. While you can always omit files from revision control simply by not staging them, having an 'ignore-list' is more convenient, especially if there are files inside the working folder that are not suitable for revision control (e.g., temporary log files) or files you want to prevent from accidentally including in a commit (files containing confidential information).
A repo-specific ignore-list of files can be specified in a .gitignore
file, stored in the root of the repo folder.
The .gitignore
file itself can be either revision controlled or ignored.
.gitignore
file changes over time), simply commit it as you would commit any other file..gitignore
file itself.The .gitignore
file supports file patterns e.g., adding temp/*.tmp
to the .gitignore
file prevents Git from tracking any .tmp
files in the temp
directory.
SIDEBAR: .gitignore
File Syntax
Blank lines: Ignored and can be used for spacing.
Comments: Begin with #
(lines starting with # are ignored).
# This is a comment
Write the name or pattern of files/directories to ignore.
log.txt # Ignores a file named log.txt
Wildcards:
*
matches any number of characters, except /
(i.e., for matching a string within a single directory level):abc/*.tmp # Ignores all .tmp files in abc directory
**
matches any number of characters (including /
)**/foo.tmp # Ignores all foo.tmp files in any directory
?
matches a single characterconfig?.yml # Ignores config1.yml, configA.yml, etc.
[abc]
matches a single character (a, b, or c)file[123].txt # Ignores file1.txt, file2.txt, file3.txt
Directories:
/
to match directories.logs/ # Ignores the logs directory
/
match files/folders recursively.*.bak # Ignores all .bak files anywhere
/
are relative to the .gitignore
location./secret.txt # Only ignores secret.txt in the root directory
Negation: Use !
at the start of a line to not ignore something.
*.log # Ignores all .log files
!important.log # Except important.log
Example:
# Ignore all log files
*.log
# Ignore node_modules folder
node_modules/
# Don’t ignore main.log
!main.log
1 Add a file into your repo's working folder that you presumably do not want to revision-control e.g., a file named temp.txt
. Observe how Git has detected the new file.
Add a few other files with .tmp
extension.
2 Configure Git to ignore those files:
Create a file named .gitignore
in the working directory root and add the text temp.txt
into it.
echo "temp.txt" >> .gitignore
temp.txt
Observe how temp.txt
is no longer detected as 'untracked' by running the git status
command (but now it will detect the .gitignore
file as 'untracked'.
Update the .gitignore
file as follows:
temp.txt
*.tmp
Observe how .tmp
files are no longer detected as 'untracked' by running the git status
command.
The file should be currently listed under Unstaged files
. Right-click it and choose Ignore...
. Choose Ignore exact filename(s)
and click OK
.
Also take note of other options available e.g., Ignore all files with this extension
etc. They may be useful in future.
Note how the temp.text
is no longer listed under Unstaged files
. Observe that a file named .gitignore
has been created in the working directory root and has the following line in it. This new file is now listed under Unstaged files
.
temp.txt
Right-click on any of the .tmp
files you added, and choose Ignore...
as you did previously. This time, choose the option Ignore files with this extension
.
Note how .temp
files are no longer shown as unstaged files, and the .gitignore
file has been updated as given below:
temp.txt
*.tmp
3 Optionally, stage and commit the .gitignore
file.
done!
Files recommended to be omitted from version control
*.class
, *.jar
, *.exe
.idea/
)GitHub allows you to create a remote copy of another remote repo, called forking.
A fork is a copy of a remote repository created on the same hosting service such as GitHub, GitLab, or Bitbucket. On GitHub, you can fork a repository from another user or organisation into your own space (i.e., your user account or an organisation you have sufficient access to). Forking is particularly useful if you want to experiment with a repo but don’t have write permissions to the original -- you can fork it and work on your own remote copy without affecting the original repository.
Preparation Create a GitHub account if you don't have one yet.
1 Go to the GitHub repo you want to fork e.g., samplerepo-things
2 Click on the button in the top-right corner. In the next step,
[ ] Copy the master branch only
option, so that you get copies of other branches (if any) in the repo.done!
Forking is not a Git feature, but a feature provided by hosted Git services like GitHub, GitLab, or Bitbucket.
GitHub does not allow you to fork the same repo more than once to the same destination. If you want to re-fork, you need to delete the previous fork.
The next step is to create a local copy of the remote repo, by cloning the remote repo.
You can clone a repository to create a full copy of it on your computer. This copy includes the entire revision history, branches, and files of the original, so it behaves just like the original repository. For example, you can clone a repository from a hosting service like GitHub to your computer, giving you a complete local version to work with.
Cloning a repo automatically creates a remote named origin which points to the repo you cloned from.
The repo you cloned from is often referred to as the upstream repo.
1 Clone the remote repo to your computer. For example, you can clone the samplerepo-things repo, or the fork you created from it in a previous lesson.
Note that the URL of the GitHub project is different from the URL you need to clone a repo in that GitHub project. e.g.
https://github.com/se-edu/samplerepo-things # GitHub project URL
https://github.com/se-edu/samplerepo-things.git # the repo URL
You can use the git clone <repository-url> [directory-name]
command to clone a repo.
<repository-url>
: The URL of the remote repository you want to copy.[directory-name]
(optional): The name of the folder where you want the repository to be cloned. If you omit this, Git will create a folder with the same name as the repository.git clone https://github.com/se-edu/samplerepo-things.git # if using HTTPS
git clone git@github.com:se-edu/samplerepo-things.git # if using SSH
git clone https://github.com/foo/bar.git my-bar-copy # also specifies a dir to use
For exact steps for cloning a repo from GitHub, refer to this GitHub document.
File
→ Clone / New ...
and provide the URL of the repo and the destination directory.
File
→ New ...
→ Choose as shown below → Provide the URL of the repo and the destination directory in the next dialog.
2 Verify the clone has a remote named origin
pointing to the upstream repo.
Use the git remote -v
command that you learned earlier.
Choose Repository
→ Repository Settings
menu option.
done!
When there are new changes in the remote, you need to pull those changes down to your local repo.
There are two steps to bringing over changes from a remote repository into a local repository: fetch and merge.
1 Clone the repo se-edu/samplerepo-finances. It has 3 commits. Your clone now has a remote origin
pointing to the remote repo you cloned from.
2 Change the remote origin
to point to samplerepo-finances-2. This remote repo is a copy of the one you cloned, but it has two extra commits.
git remote set-url origin https://github.com/se-edu/samplerepo-finances-2.git
Go to Repository
→ Repository settings ...
to update remotes.
3 Verify the local repo is unaware of the extra commits in the remote.
git status
On branch master
Your branch is up to date with 'origin/master'.
nothing to commit, working tree clean
The revision graph should look like the below:
If it looks like the below, it is possible that Sourcetree is auto-fetching data from the repo periodically.
4 Fetch from the new remote.
Use the git fetch <remote>
command to fetch changes from a remote. If the <remote>
is not specified, the default remote origin
will be used.
git fetch origin
remote: Enumerating objects: 8, done.
... # more output ...
afbe966..cc6a151 master -> origin/master
* [new tag] beta -> beta
Click on the Fetch
button on the top menu:
5 Verify the fetch worked i.e., the local repo is now aware of the two missing commits. Also observe how the local branch ref of the master
branch, the staging area, and the working directory remain unchanged after the fetch.
Use the git status
command to confirm the repo now knows that it is behind the remote repo.
git status
On branch master
Your branch is behind 'origin/master' by 2 commits, and can be fast-forwarded.
(use "git pull" to update your local branch)
nothing to commit, working tree clean
Now, the revision graph should look something like the below. Note how the origin/master
ref is now two commits ahead of the master
ref.
6 Merge the fetched changes.
Use the git merge <remote-tracking-branch>
command to merge the fetched changes. Check the status and the revision graph to verify that the branch tip has now moved by two more commits.
git merge origin/master
git status
git log --oneline --decorate
To merge the fetched changes, right-click on the latest commit on origin/remote
branch and choose Merge
.
In the next dialog, choose as follows:
The final result should be something like the below (same as the repo state before we started this hands-on practical):
Note that merging the fetched changes can get complicated if there are multiple branches or the commits in the local repo conflict with commits in the remote repo. We will address them when we learn more about Git branches, in a later lesson.
done!
Pull is a shortcut that combines fetch and merge — it fetches the latest changes from the remote and immediately merges them into your current branch. In practice, Git users typically use the pull instead of the fetch-then-merge.
pull = fetch + merge
1 Similar to the previous hands-on practical, clone the repo se-edu/samplerepo-finances (to a new location).
Change the remote origin
to point to samplerepo-finances-2.
2 Pull the newer commits from the remote, instead of a fetch-then-merge.
Use the git pull <remote> <branch>
command to pull changes.
git pull origin master
The following works too. If the <remote>
and <branch>
are not specified, Git will pull to the current branch from the remote branch it is tracking.
git pull
Click on the Pull
button on the top menu:
3 Verify the outcome is same as the fetch + merge steps you did in the previous hands-on practical.
done!
You can pull from any number of remote repos, provided the repos involved have a shared history. This can be useful when the upstream repo you forked from has some new commits that you wish to bring over to your copies of the repo (i.e., your fork and your local repo).
Preparation Fork se-edu/samplerepo-finances to your GitHub account.
Clone your fork to your computer.
Now, let's pretend that there are some new commits in upstream repo that you would like to bring over to your fork, and your local repo. Here are the steps:
1 Add the upstream repo se-edu/samplerepo-finances as remote named upstream
in your local repo.
Adding remotes was covered in Lesson T2L4. Linking a Local Repo With a Remote Repo
2 Pull from the upstream repo. If there are new commits (in this case, there will be none), those will come over to your local repo. For example:
git pull upstream master
3 Push to your fork. Any new commits you pulled from the upstream repo will now appear in your fork as well. For example:
git push origin master
The method given above is the more 'standard' method of synchronising a fork with the upstream repo. In addition, platforms such as GitHub can provide other ways (example: GitHub's Sync fork feature).
4 For good measure, let's pull from another repo.
other-upstream
in your local repo.git remote add other-upstream https://github.com/se-edu/samplerepo-finances-2.git
git pull other-upstream master
git push origin master
done!
It is useful to be able to see what changes were included in a specific commit.
When you examine a commit, normally what you see is the 'changes made since the previous commit'. This does not mean that a Git commit contains only the changes made since the previous commit. As you recall, a Git commit contains a full snapshot of the working directory. However, tools used to examine commits typically show only the changes, as that is the more informative part.
Git shows changes included in a commit by dynamically calculating the difference between the snapshots stored in the target commit and the parent commit. This is because Git commits store snapshots of the working directory, not changes themselves.
Although each commit represents a copy of the entire working directory, Git uses space efficiently in two main ways:
To address a specific commit, you can use its SHA (e.g., e60deaeb2964bf2ebc907b7416efc890c9d4914b
). In fact, just the first few characters of the SHA is enough to uniquely address a commit (e.g., e60deae
), provided the partial SHA is long enough to uniquely identify the commit (i.e., only one commit has that partial SHA).
Naturally, a commit can be addressed using any ref pointing to it too (e.g., HEAD
, master
).
Another related technique is to use the <ref>~<n>
notation (e.g., HEAD~1
) to address the commit that is n
commits prior to the commit pointed by <ref>
i.e., "start with the commit pointed by <ref>
and go back n
commits".
A related alternative notation is HEAD~
, HEAD~~
, HEAD~~~
, ... to mean HEAD~1
, HEAD~2
, HEAD~3
etc.
HEAD
or master
HEAD~1
or master~1
or HEAD~
or master~
HEAD~2
or master~2
Git uses the diff format to show file changes in a commit. The diff format was originally developed for Unix. It was later extended with headers and metadata to show changes between file versions and commits. Here is an example diff showing the changes to a file.
diff --git a/fruits.txt b/fruits.txt
index 7d0a594..f84d1c9 100644
--- a/fruits.txt
+++ b/fruits.txt
@@ -1,6 +1,6 @@
-apples
+apples, apricots
bananas
cherries
dragon fruits
-elderberries
figs
@@ -20,2 +20,3 @@
oranges
+pears
raisins
diff --git a/colours.txt b/colours.txt
new file mode 100644
index 0000000..55c8449
--- /dev/null
+++ b/colours.txt
@@ -0,0 +1 @@
+a file for colours
A Git diff can consist of multiple file diffs, one for each changed file. Each file diff can contain one or more hunk i.e., a localised group of changes within the file — including lines added, removed, or left unchanged (included for context).
Given below is how the above diff is divided into its components:
File diff for fruits.txt
:
diff --git a/fruits.txt b/fruits.txt
index 7d0a594..f84d1c9 100644
--- a/fruits.txt
+++ b/fruits.txt
Hunk 1:
@@ -1,6 +1,6 @@
-apples
+apples, apricots
bananas
cherries
dragon fruits
-elderberries
figs
Hunk 2:
@@ -20,2 +20,3 @@
oranges
+pears
raisins
File diff for colours.txt
:
diff --git a/colours.txt b/colours.txt
new file mode 100644
index 0000000..55c8449
--- /dev/null
+++ b/colours.txt
Hunk 1:
@@ -0,0 +1 @@
+a file for colours
Here is an explanation of the diff:
Part of Diff | Explanation |
---|---|
diff --git a/fruits.txt b/fruits.txt | The diff header, indicating that it is comparing the file fruits.txt between two versions: the old (a/ ) and new (b/ ). |
index 7d0a594..f84d1c9 100644 | Shows the before and after the change, and the file mode (100 means a regular file, 644 are file permission indicators). |
--- a/fruits.txt +++ b/fruits.txt | Marks the old version of the file (a/fruits.txt ) and the new version of the file (b/fruits.txt ). |
| This hunk header shows that lines 1-6 (i.e., starting at line 1 , showing 6 lines) in the old file were compared with lines 1–6 in the new file. |
-apples +apples, apricots | Removed line apples and added line apples, apricots . |
bananas cherries dragon fruits | Unchanged lines, shown for context. |
-elderberries | Removed line: elderberries . |
figs | Unchanged line, shown for context. |
| Hunk header showing that lines 20-21 in the old file were compared with lines 20–22 in the new file. |
oranges +pears raisins | Unchanged line. Added line: pears .Unchanged line. |
diff --git a/colours.txt b/colours.txt | The usual diff header, indicates that Git is comparing two versions of the file colours.txt : one before and one after the change. |
new file mode 100644 | This is a new file being added. 100644 means it’s a normal, non-executable file with standard read/write permissions. |
index 0000000..55c8449 | The usual SHA hashes for the two versions of the file. 0000000 indicates the file did not exist before. |
--- /dev/null +++ b/colours.txt | Refers to the "old" version of the file (/dev/null means it didn’t exist before), and the new version. |
@@ -0,0 +1 @@ | Hunk header, saying: “0 lines in the old file were replaced with 1 line in the new file, starting at line 1.” |
+a file for colours | Added line |
Points to note:
+
indicates a line being added.-
indicates a line being deleted.TargetView contents of specific commits in a repo.
Preparation You can use any repo that has commits e.g., the things
repo.
1 Locate the commits to view, using the revision graph.
git log --oneline --decorate
e60deae (HEAD -> master, origin/master) Update fruits list
f761ea6 Add colours.txt, shapes.txt
2bedace Add figs to fruits.txt
d5f91de Add fruits.txt
2 Use the git show
command to view specific commits.
git show # shows the latest commit
commit e60deaeb2964bf2ebc907b7416efc890c9d4914b (HEAD -> master, origin/master)
Author: damithc <...@...>
Date: Sat Jun ...
Update fruits list
diff --git a/fruits.txt b/fruits.txt
index 7d0a594..6d502c3 100644
--- a/fruits.txt
+++ b/fruits.txt
@@ -1,6 +1,6 @@
-apples
+apples, apricots
bananas
+blueberries
cherries
dragon fruits
-elderberries
figs
To view the parent commit of the latest commit, you can use any of these commands:
git show HEAD~1
git show master~1
git show e60deae # first few characters of the SHA
git show e60deae..... # run git log to find the full SHA and specify the full SHA
To view the commit that is two commits before the latest commit, you can use git show HEAD~2
etc.
Click on the commit. The remaining panels (indicated in the image below) will be populated with the details of the commit.
done!
PRO-TIP: Use Git Aliases to Work Faster
The Git alias feature allows you to create custom shortcuts for frequently used Git commands. This saves time and reduces typing, especially for long or complex commands. Once an alias is defined, you can use the alias just like any other Git command e.g., use git lodg
as an alias for git log --oneline --decorate --graph
.
To define a global git alias, you can use the git config --global alias.<alias> "command"
command. e.g.,
git config --global alias.lodg "log --oneline --graph --decorate"
You can also create shell-level aliases using your shell configuration (e.g., .bashrc
, .zshrc
) to make even shorter aliases. This lets you create shortcuts for any command, including Git commands, and even combine them with other tools. e.g., instead of the Git alias git lodg
, you can define a shorter shell-level alias glodg
.
1. Locate your .bash_profile
file (likely to be in : C:\Users\<YourName>\.bash_profile
-- if it doesn’t exist, create it.)
1. Locate your shell's config file e.g., .bashrc
or .zshrc
(likely to be in your ~
folder)
1. Locate your shell's config file e.g., .bashrc
or .zshrc
(likely to be in your ~
folder)
Oh-My-Zsh for Zsh terminal supports a Git plugin that adds a wide array of Git command aliases to your terminal.
2. Add aliases to that file:
alias gs='git status'
alias glod='git log --oneline --graph --decorate'
3. Apply changes by running the command source ~/.zshrc
or source ~/.bash_profile
or source ~/.bashrc
, depending on which file you put the aliases in.
When working with many commits, it helps to tag specific commits with custom names so they’re easier to refer to later.
Git lets you tag commits with names, making them easy to reference later. This is useful when you want to mark specific commits -- such as releases or key milestones (e.g., v1.0
or v2.1
). Using tags to refer to commits is much more convenient than using SHA hashes. In the diagram below, v1.0 and interim are tags.
A tag stays fixed to the commit. Unlike branch refs or HEAD
, tags do not move automatically as new commits are made. As you see below, after adding a new commit, tags stay in the previous commits while master←HEAD has moved to the new commit.
Git supports two kinds of tags:
Annotated tags are generally preferred for versioning and public releases, while lightweight tags are often used for less formal purposes, such as marking a commit for your own reference.
Target Add a few tags to a repository.
Preparation Fork and clone the samplerepo-preferences. Use the cloned repo on your computer for the following steps.
1 Add a lightweight tag to the current commit as v1.0
:
git tag v1.0
2 Verify the tag was added. To view tags:
git tag
v1.0
To view tags in the context of the revision graph:
git log --oneline --decorate
507bb74 (HEAD -> master, tag: v1.0, origin/master, origin/HEAD) Add donuts
de97f08 Add cake
5e6733a Add bananas
3398df7 Add food.txt
3 Use the tag to refer to the commit e.g., git show v1.0
should show the changes in the tagged commit.
4 Add an annotated tag to an earlier commit. The example below adds a tag v0.9
to the commit HEAD~2
with the message First beta release
. The -a
switch tells Git this is an annotated tag.
git tag -a v0.9 HEAD~2 -m "First beta release"
5 Check the new annotated tag. While both types of tags appear similarly in the revision graph, the show
command on an annotated tag will show the details of the tag and the details of the commit it points to.
git show v0.9
tag v0.9
Tagger: ... <...@...>
Date: Sun Jun ...
First beta release
commit ....999087124af... (tag: v0.9)
Author: ... <...@...>
Date: Sat Jun ...
Add figs to fruits.txt
diff --git a/fruits.txt b/fruits.txt
index a8a0a01..7d0a594 100644
# rest of the diff goes here
Right-click on the commit (in the graphical revision graph) you want to tag and choose Tag…
.
Specify the tag name e.g., v1.0
and click Add Tag
.
Configure tag properties in the next dialog and press Add
. For example, you can choose whether to make it a lightweight tag or an annotated tag (default).
Tags will appear as labels in the revision graph, as seen below. To see the details of an annotated tag, you need to use the menu indicated in the screenshot.
done!
If you need to change what a tag points to, you must delete the old one and create a new tag with the same name. This is because tags are designed to be fixed references to a specific commit, and there is no built-in mechanism to 'move' a tag.
Preparation Continue with the same repo you used for the previous hands-on practical.
Move the v1.0
tag to the commit HEAD~1
, by deleting it first and creating it again at the destination commit.
Delete the previous v1.0
tag by using the -d
. Add it again to the other commit, as before.
git tag -d v1.0
git tag v1.0 HEAD~1
The same dialog used to add a tag can be used to delete and even move a tag. Note that the 'moving' here translates to deleting and re-adding behind the scene.
done!
Tags are different from commit messages, in purpose and in form. A commit message is a description of the commit that is part of the commit itself. A tag is a short name for a commit, which you can use to address a commit.
Pushing commits to a remote does not push tags automatically. You need to push tags specifically.
Target Push tags you created earlier to the remote.
Preparation Continue with the same repo you used for the previous hands-on practical.
You can go to your remote on GitHub link https://github.com/{USER}/{REPO}/tags
(e.g., https://github.com/johndoe/samplerepo-preferences/tags
) to verify the tag is present there.
Note how GitHub assumes these tags are meant as releases, and automatically provides zip and tar.gz archives of the repo (as at that tag).
1 Push a specific tag in the local repo to the remote (e.g., v1.0
) using the git push <origin> <tag-name>
command.
git push origin v1.0
In addition to verifying the tag's presence via GitHub, you can also use the following command to list the tags presently in the remote.
git ls-remote --tags origin
2 Delete a tag in the remote, using the git push --delete <remote> <tag-name>
command.
git push --delete origin v1.0
3 Push all tags to the remote repo, using the git push <remote> --tags
command.
git push origin --tags
To push a specific tag, use the following menu:
To push all tags, you can tick the Push all tags
option when pushing commits:
done!
Git can tell you the net effect of changes between two points of history.
Git's diff feature can show you what changed between two points in the revision history. Given below are some use cases.
Usage 1: Examining changes in the working directory
Example use case: To verify the next commit will include exactly what you intend it to include.
Preparation For this, you can use the things
repo you created earlier. If you don't have it, you can clone a copy of a similar repo given here.
1 Do some changes to the working directory. Stage some (but not all) changes. For example, you can run the following commands.
echo -e "blue\nred\ngreen" >> colours.txt
git add . # a shortcut to stage all changes
echo "no shapes added yet" >> shapes.txt
2 Examine the staged and unstaged changes.
The git diff
command shows unstaged changes in the working directory (tracked files only). The output of the diff
command, is a diff view (introduced in this lesson).
git diff
diff --git a/shapes.txt b/shapes.txt
index 5c2644b..949c676 100644
--- a/shapes.txt
+++ b/shapes.txt
@@ -1 +1,2 @@
a file for shapes
+no shapes added yet!
The git diff --staged
command shows the staged changes (same as git diff --cached
).
git diff --staged
Select the two commits: Click on one commit, and Ctrl-Click (or Cmd-Click) on the second commit. The changes between the two selected commits will appear in the other panels, as shown below:
done!
Usage 2: Comparing two commits at different points of the revision graph
Example use case: Suppose you’re trying to improve the performance of a piece of software by experimenting with different code tweaks. You commit after each change (as you should). After several commits, you now want to review the overall effect of all those changes on the code.
Target Compare two commits in a repo.
Preparation You can use any repo with multiple commits e.g., the things
repo.
You can use the git diff <commit1> <commit2>
command for this.
..
notation to specify the commit range too e.g., 0023cdd..fcd6199
, HEAD~2..HEAD
git diff v0.9 HEAD
diff --git a/colours.txt b/colours.txt
new file mode 100644
index 0000000..55c8449
--- /dev/null
+++ b/colours.txt
@@ -0,0 +1 @@
+a file for colours
# rest of the diff ...
Swap the commit order in the command and see what happens.
git diff HEAD v0.9
diff --git a/colours.txt b/colours.txt
deleted file mode 100644
index 55c8449..0000000
--- a/colours.txt
+++ /dev/null
@@ -1 +0,0 @@
-a file for colours
# rest of the diff ...
As you can see, the diff
is directional i.e., diff <commit1> <commit2>
shows what changes you need to do to go from the <commit1>
to <commit2>
. If you swap <commit1>
and <commit2>
, the output will change accordingly e.g., lines previously shown as 'added' will now be shown as 'deleted'.
Select the two commits: Click on one commit, and Ctrl-Click (or Cmd-Click) on the second commit. The changes between the two selected commits will appear in the other panels, as shown below:
The same method can be used to compare the current state of the working directory (which might have uncommitted changes) to a point in the history.
done!
Usage 3: Examining changes to a specific file
Example use case: Similar to other use cases but when you are interested in a specific file only.
Target Examine the changes done to a file between two different points in the version history (including the working directory).
Preparation Use any repo with multiple commits e.g. the things
repo.
Add the -- path/to/file
to a previous diff command to narrow the output to a specific file. Some examples:
git diff -- fruits.txt # unstaged changes to fruits.txt
git diff --staged -- src/main.java # staged changes to src/main.java
git diff HEAD~2..HEAD -- fruits.txt # changes to fruits.txt between commits
Sourcetree UI shows changes to one file at a time by default; just click on the file to view changes to that file. To view changes to multiple files, Ctrl-Click (or Cmd-Click) on multiple files to select them.
done!
Another useful feature of revision control is to be able to view the working directory as it was at a specific point in history, by checking out a commit created at that point.
Suppose you added a new feature to a software product, and while testing it, you noticed that another feature added two commits ago doesn’t handle a certain edge case correctly. Now you’re wondering: did the new feature break the old one, or was it already broken? Can you go back to the moment you committed the old feature and test it in isolation, and come back to the present after you found the answer? With Git, you can.
To view the working directory at a specific point in history, you can check out a commit created at that point.
When you check out a commit, Git:
HEAD
ref to that commit, marking it as the current state you’re viewing.→
[check out commit C2
...]
Checking out a specific commit puts you in a "detached HEAD
" state: i.e., the HEAD
no longer points to a branch, but directly to a commit (see the above diagram for an example). This isn't a problem by itself, but any commits you make in this state can be lost, unless certain follow-up actions are taken. It is perfectly fine to be in a detached state if you are only examining the state of the working directory at that commit.
To get out of a "detached HEAD" state, you can simply check out a branch, which "re-attaches" HEAD
to the branch you checked out.
→
[check out master
...]
Target Checkout a few commits in a local repo, while examining the working directory to verify that it matches the state when you created the corresponding commit
Preparation Use any repo with commits e.g., the things
repo
1 Examine the revision tree, to get your bearing first.
git log --oneline --decorate
Reminder: You can use aliases to reduce typing Git commands.
e60deae (HEAD -> master, origin/master) Update fruits list
f761ea6 (tag: v1.0) Add colours.txt, shapes.txt
2bedace (tag: v0.9) Add figs to fruits.txt
d5f91de Add fruits.txt
2 Use the checkout <commit-identifier>
command to check out a commit other than the one currently pointed by HEAD
. You can use any of the following methods:
git checkout v1.0
: checks out the commit tagged v1.0
git checkout 0023cdd
: checks out the commit with the hash 0023cdd
git checkout HEAD~2
: checks out the commit 2 commits behind the most recent commit.git checkout HEAD~2
Note: switching to 'HEAD~2'.
You are in 'detached HEAD' state.
# rest of the warning about the detached head ...
HEAD is now at 2bedace Add figs to fruits.txt
3 Verify HEAD
and the working directory have updated as expected.
HEAD
should now be pointing at the target commitshapes.txt
should not be in the folder).git log --oneline --decorate
2bedace (HEAD, tag: v0.9) Add figs to fruits.txt
d5f91de Add fruits.txt
HEAD
is indeed pointing at the target commit.
But note how the output does not show commits you added after the checked-out commit.
The --all
switch tells git log
to show commits from all refs, not just those reachable from the current HEAD
. This includes commits from other branches, tags, and remotes.
git log --oneline --decorate --all
e60deae (origin/master, master) Update fruits list
f761ea6 (tag: v1.0) Add colours.txt, shapes.txt
2bedace (HEAD, tag: v0.9) Add figs to fruits.txt
d5f91de Add fruits.txt
4 Go back to the latest commit by checking out the master
branch again.
git checkout master
In the revision graph, double-click the commit you want to check out, or right-click on that commit and choose Checkout...
.
Click OK
to the warning about ‘detached HEAD’ (similar to below).
The specified commit is now loaded onto the working folder, as indicated by the HEAD
label.
To go back to the latest commit on the master
branch, double-click the master
branch.
If you check out a commit that comes before the commit in which you added a certain file (e.g., temp.txt
) to the .gitignore
file, and if the .gitignore
file is version controlled as well, Git will now show it under ‘unstaged modifications’ because at Git hasn’t been told to ignore that file yet.
done!
If there are uncommitted changes in the working directory, Git proceeds with a checkout only if it can preserve those changes.
The Git stash feature temporarily sets aside uncommitted changes you’ve made (in your working directory and staging area), without committing them. This is useful when you’re in the middle of some work, but need to switch to another state (e.g., checkout a previous commit), and your current changes are not yet ready to be committed or discarded. You can later reapply the stashed changes when you’re ready to resume that work.
Git can also reset the revision history to a specific point so that you can start over from that point.
Suppose you realise your last few commits have gone in the wrong direction, and you want to go back to an earlier commit and continue from there — as if the “bad” commits never happened. Git’s reset feature can help you do that.
Git reset moves the tip of the current branch to a specific commit, optionally adjusting your staged and unstaged changes to match. This effectively rewrites the branch's history by discarding any commits that came after that point.
Resetting is different from the checkout feature:
HEAD
ref.→
[reset to C2
...]
master
branch!There are three types of resets: soft, mixed, hard. All three move the branch pointer to a new commit, but they vary based on what happens to the staging area and the working directory.
Preparation First, set the stage as follows (e.g., in the things
repo):
i) Add four commits that are supposedly 'bad' commits.
ii) Do a 'bad' change to one file and stage it.
iii) Do a 'bad' change to another file, but don't stage it.
The following commands can be used to add commits B1
-B4
:
echo "bad colour" >> colours.txt
git commit -am "Incorrectly update colours.txt"
echo "bad shape" >> shapes.txt
git commit -am "Incorrectly update shapes.txt"
echo "bad fruit" >> fruits.txt
git commit -am "Incorrectly update fruits.txt"
echo "bad line" >> incorrect.txt
git add incorrect.txt
git commit -m "Add incorrect.txt"
echo "another bad colour" >> colours.txt
git add colours.txt
echo "another bad shape" >> shapes.txt
Now we have some 'bad' commits and some 'bad' changes in both the staging area and the working directory. Let's use the reset feature to get rid of all of them, but do it in three steps so that you can learn all three types of resets.
1 Do a soft reset to B2
(i.e., discard last two commits). Verify,
master
branch is now pointing at B2
, and,B3
and B4
) are now in the staging area.Use the git reset --soft <commit>
command to do a soft reset.
git reset --soft HEAD~2
You can run the following commands to verify the current status of the repo is as expected.
git status # check overall status
git log --oneline --decorate # check the branch tip
git diff # check unstaged changes
git diff --staged # check staged changes
Right-click on the commit that you want to reset to, and choose Reset <branch-name> to this commit
option.
In the next dialog, choose Soft - keep all local changes
.
2 Do a mixed reset to commit B1
. Verify,
master
branch is now pointing at B1
.incorrect.txt
appears as an 'untracked' file -- this is because unstaging a change of type 'add file' results in an untracked file.Use the git reset --mixed <commit>
command to do a mixed reset. The --mixed
flag is the default, and can be omitted.
git reset HEAD~1
Verify the repo status, as before.
Similar to the previous reset, but choose the Mixed - keep working copy but reset index
option in the reset dialog.
3 Do a hard reset to commit C4
. Verify,
master
branch is now pointing at C4
i.e., all 'bad' commits are gone.incorrect.txt
-- Git leaves untracked files alone, as untracked files are not meant to be under Git's control).Use the git reset --hard <commit>
command.
git reset --hard HEAD~1
Verify the repo status, as before.
Similar to the previous reset, but choose the Hard - discard all working copy changes
option.
done!
Rewriting history can cause your local repo to diverge from its remote counterpart. For example, if you discard earlier commits and create new ones in their place, and you’ve already pushed the original commits to a remote repository, your local branch history will no longer match the corresponding remote branch. Git refers to this as a diverged history.
To protect the integrity of the remote, Git will reject attempts to push a diverged branch using a normal push. If you want to overwrite the remote history with your local version, you must perform a force push.
Preparation Choose a local-remote repo pair under your control e.g., the things
repo from Tour 2: Backing up a Repo on the Cloud.
1 Rewrite the last commit: Reset the current branch back by one commit, and add a new commit.
For example, you can use the following commands.
git reset --hard HEAD~1
echo "water" >> drinks.txt
git add .
git commit -m "Add drinks.txt"
2 Observe how the local branch is diverged.
git log --oneline --graph --all
* fc1d04e (HEAD -> master) Add drinks.txt
| * e60deae (upstream/master, origin/master) Update fruits list
|/
* f761ea6 (tag: v1.0) Add colours.txt, shapes.txt
* 2bedace (tag: v0.9) Add figs to fruits.txt
* d5f91de Add fruits.txt
3 Attempt to push to the remote. Observe Git rejects the push.
git push origin master
To https://github.com/.../things.git
! [rejected] master -> master (non-fast-forward)
error: failed to push some refs to 'https://github.com/.../things.git'
hint: Updates were rejected because the tip of your current branch is behind
hint: its remote counterpart. If you want to integrate the remote changes,
hint: ...
4 Do a force-push.
You can use the --force
(or -f
) flag to force push.
git push -f origin master
A safer alternative to --force
is --force-with-lease
which overwrites the remote branch only if it hasn’t changed since you last fetched it (i.e., only if remote doesn't have recent changes that you are unaware of):
git push --force-with-lease origin master
done!
To create well-crafted commits, you need to know how to control which precise changes go into a commit.
Crafting a commit involves two aspects:
SIDEBAR: Guidelines on what to include in a commit
A good commit represents a single, logical unit of change — something that can be described clearly in one sentence. For example, fixing a specific bug, adding a specific feature, or refactoring a specific function. If each commit tells a clear story about why the change was made and what it achieves, your repository history becomes a valuable narrative of the project’s development. Here are some (non-exhaustive) guidelines:
Git can let you choose not just which files, but which specific changes within those files, to include in a commit. Most Git tools — including the command line and many GUIs — let you interactively select which "hunks" or even individual lines of a file to stage. This allows you to separate unrelated changes and avoid committing unnecessary edits. If you make multiple changes in the same file, you can selectively stage only the parts that belong to the current logical change.
This level of control is particularly useful when:
Preparation You can use any repo for this.
1 Do several changes to some tracked files. Change multiple files. Also change multiple locations in the same file.
2 Stage some changes in some files while keeping other changes in the same files unstaged.
As you know, you can use git add <filename>
to stage changes to an entire file.
To select which hunks to stage, you can use the git add -p
command instead (-p
stands for 'by patch'):
git add -p
This command will take you to an interactive mode in which you can go through each hunk and decide if you want to stage it. The video below contains a demonstration of how this feature works:
To stage a hunk, you can click the Stage
button above the hunk in question:
Most git operations can be done faster through the CLI than equivalent Git GUI clients, once you are familiar enough with the CLI commands.
However, selective staging is one exception where a good GUI can do better than the CLI, if you need to do many fine-grained staging operations (e.g., frequently staging only parts of hunks).
done!
Detailed and well-written commit messages can increase the value of Git revision history.
Every commit you make in Git also includes a commit message that explains the change. While one-line messages are fine for small or obvious changes, as your revision history grows, good commit messages become an important source of information — for example, to understand the rationale behind a specific change made in the past.
A commit message is meant to explain the intent behind the changes, not just what was changed. The code (or diff) already shows what changed. Well-written commit messages make collaboration, code reviews, debugging, and future maintenance easier by helping you and others quickly understand the project’s history without digging into the code of every commit.
A complete commit message can include a short summary line (the subject) followed by a more detailed body if needed. The subject line should be a concise description of the change, while the body can elaborate on the context, rationale, side effects, or other details if the change is more complex.
A commit message has the following structure (note how the subject and the body are separated by a blank line):
Subject line
<blank line>
Body
# lines starting with '#' are ignored (they will not be included in the commit message)
Here is an example commit message:
Find command: make matching case-insensitive
Find command is case-sensitive.
A case-insensitive find is more user-friendly because users cannot be
expected to remember the exact case of the keywords.
Let's,
* update the search algorithm to use case-insensitive matching
* add a script to migrate stress tests to the new format
Do some changes to a repo you have.
Commit the changes while writing a full commit message (i.e., subject + body).
When you are ready to commit, use the git commit
command (without specifying a commit message).
git commit
This will open your default text editor (like Vim, Nano, or VS Code). Write the commit message inside the editor.
Save and close the editor to create the commit.
You can write your full commit message in the textbox you have been using to write commit messages already.
done!
Following a style guide makes your commit messages more consistent and fit-for-purpose. Many teams adopt established guidelines. These style guides typically contain common conventions that Git users follow when writing commit messages. For example:
Fix typo in README
rather than Fixed typo
or Fixes typo
).PRO-TIP: Configure Git to use your preferred text editor
Git will use the default text editor when it needs you to write a commit message. However, Git can be configured to use a different text editor of your choice.
You can use the following command to set the Git's default text editor:
git config --global core.editor "<editor command>"
Some examples for <editor command>
Editor | Command to use |
---|---|
Vim (default) | vim |
Nano | nano |
VS Code | code --wait e.g., git config --global core.editor "code --wait" For this to work, your computer should already be configured to launch VS Code using the code command. See here to find how (refer the 'Launching from command line' section). |
Sublime Text | subl -n -w |
Atom | atom --wait |
Notepad++ | notepad++.exe (Windows only) |
Notepad | notepad (Windows built-in) |
Why use --wait
or -w
? Graphical editors (like VS Code or Sublime) start a separate process, which can take a few seconds. Without --wait
, Git may think editing is done before you actually write the message. --wait
makes Git pause until the editor window is closed.
When the revision history gets 'messy', Git has a way to 'tidy up' the recent commits.
Git has a powerful tool called interactive rebasing which lets you review and reorganise your recent commits. With it, you can reword commit messages, change their order, delete commits, combine several commits into one (squash), or split a commit into smaller pieces. This feature is useful for tidying up a commit history that has become messy — for example, when some commits are out of order, poorly described, or include changes that would be clearer if split up or combined.
Preparation Run the following commands to create a sample repo that we'll be using for this hands-on practical:
mkdir samplerepo-sitcom
cd samplerepo-sitcom
git init
echo "Aspiring actress" >> Penny.txt
git add .
git commit -m "C1: Add Penny.txt"
echo "Scientist" >> Sheldon.txt
git add .
git commit -m "C3: Add Sheldon.txt"
echo "Comic book store owner" >> Stuart.txt
git add .
git commit -m "C2: Add Stuart.txt"
echo "Engineer" >> Stuart.txt
git commit -am "X: Incorrectly update Stuart.txt"
echo "Engineer" >> Howard.txt
git add .
git commit -m "C4: Adddd Howard.txt"
Target Here are the commits that should be in the created repo, and how each commit needs to be 'tidied up'.
C4: Adddd Howard.txt
-- Fix typo in the commit message Adddd
→ Add
.X: Incorrectly update Stuart.txt
-- Drop this commit.C2: Add Stuart.txt
-- Swap this commit with the one below.C3: Add Sheldon.txt
-- Swap this commit with the one above.C1: Add Penny.txt
-- No change required.1 Start the interactive rebasing.
To start the interactive rebase, use the git rebase -i <start-commit>
command. -i
stands for 'interactive'. In this case, we want to modify the last four commits (hence, HEAD~4
).
git rebase -i HEAD~4
pick 97a8c4a C3: Add Sheldon.txt
pick 60bd28d C2: Add Stuart.txt
pick 8b9a36f X: Incorrectly update Stuart.txt
pick 8ab6941 C4: Adddd Howard.txt
# Rebase ee04afe..8ab6941 onto ee04afe (4 commands)
#
# Commands:
# p, pick <commit> = use commit
# r, reword <commit> = use commit, but edit the commit message
# e, edit <commit> = use commit, but stop for amending
# s, squash <commit> = use commit, but meld into previous commit
# f, fixup [-C | -c] <commit> = like "squash" but keep only the previous
# commit's log message, unless -C is used, in which case
# keep only this commit's message; -c is same as -C but
# opens the editor
# x, exec <command> = run command (the rest of the line) using shell
# b, break = stop here (continue rebase later with 'git rebase --continue')
# d, drop <commit> = remove commit
# l, label <label> = label current HEAD with a name
# t, reset <label> = reset HEAD to a label
# m, merge [-C <commit> | -c <commit>] <label> [# <oneline>]
# create a merge commit using the original merge commit's
# message (or the oneline, if no original merge commit was
# specified); use -c <commit> to reword the commit message
# u, update-ref <ref> = track a placeholder for the <ref> to be updated
# to this position in the new commits. The <ref> is
# updated at the end of the rebase
#
# These lines can be re-ordered; they are executed from top to bottom.
#
# If you remove a line here THAT COMMIT WILL BE LOST.
#
# However, if you remove everything, the rebase will be aborted.
#
The command will take you to the text editor, which will present you with a wall of text similar to the above. It has two parts:
pick
indicated by default (pick
means 'use this commit in the result') for each.2 Edit the commit list to specify the rebase actions, as follows:
pick 60bd28d C2: Add Stuart.txt
pick 97a8c4a C3: Add Sheldon.txt
drop 8b9a36f X: Incorrectly update Stuart.txt
reword 8ab6941 C4: Addddd Howard.txt
4 Once you save edits and exit the text editor, Git will perform the rebase based on the actions you specified, from top to bottom.
At some steps, Git will pause the rebase and ask for your inputs. In this case, it will ask you to specify the new commit message when it is processing the following line.
reword 8ab6941 C4: Addddd Howard.txt
To go to the interactive rebase mode, right-click the parent commit of the earliest commit you want to reorganise (in this case, it is C1: Add Penny.txt
) and choose Rebase children of <SHA> interactively...
2 To indicate what action you want to perform on each commit, select the commit in the list and click on the button for the action you want to do on it:
3 To execute the rebase, after indicating the action for all commits (the dialog will look like the below), click OK
.
The final result should be something like the following, 'tidied up' exactly as we wanted:
* 727d877 C4: Add Howard.txt
* 764fc29 C3: Add Sheldon.txt
* 08a965a C2: Add Stuart.txt
* 6436598 C1: Add Penny.txt
done!
Rebasing rewrites history. It is not recommended to rebase commits you have already shared with others.
To work in parallel timelines, you can use Git branches.
Git branches let you develop multiple versions of your work in parallel — effectively creating diverged timelines of your repository’s history. For example, one team member can create a new branch to experiment with a change, while the rest of the team continues working on another branch. Branches can have meaningful names, such as master
, release
, or draft
.
A Git branch is simply a ref (a named label) that points to a commit and automatically moves forward as you add new commits to that branch. As you’ve seen before, the HEAD
ref indicates which branch you’re currently working on, by pointing to the corresponding branch ref.
When you add a commit, it goes into the branch you are currently on, and the branch ref (together with the HEAD
ref) moves to the new commit.
Git creates a branch named master
by default (Git can be configured to use a different name e.g., main
).
Given below is an illustration of how branch refs move as branches evolve. Refer to the text below it for explanations of each stage.
master
) and there is only one commit on it. The HEAD
ref is pointing to the master
branch (as we are currently on that branch).master
and the HEAD
refs have moved to the new commit.fix1
has been added. The repo has switched to the new branch too (hence, the HEAD
ref is attached to the fix1
branch).c
) has been added. The current branch ref fix1
moves to the new commit, together with the HEAD
ref.master
branch. Hence, the HEAD
has moved back to master
branch's .b
(not c
).d
) has been added. The master
and the HEAD
refs have moved to that commit.fix1
branch and added a new commit e
to it. Note how the branch ref fix1
(together with HEAD
) has moved to the new commit e
while the branch ref master
still points to d
.Note that appearance of the revision graph (colors, positioning, orientation etc.) varies based on the Git client you use, and might not match the exact diagrams given above.
Preparation Fork the samplerepo-things repo, and clone it onto your computer.
1 Observe that you are on the branch called master
.
$ git status
on branch master
2 Start a branch named feature1
and switch to the new branch.
You can use the branch
command to create a new branch and the checkout
command to switch to a specific branch.
$ git branch feature1
$ git checkout feature1
One-step shortcut to create a branch and switch to it at the same time:
$ git checkout –b feature1
The new switch
command
Git recently introduced a switch
command that you can use instead of the checkout
command given above.
To create a new branch and switch to it:
$ git branch feature1
$ git switch feature1
One-step shortcut (by using -c
or --create
flag):
$ git switch –c feature1
Click on the Branch
button on the main menu. In the next dialog, enter the branch name and click Create Branch
.
Note how the feature1
is indicated as the current branch (reason: Sourcetree automatically switches to the new branch when you create a new branch, if the Checkout New Branch
was selected in the previous dialog).
3 Create some commits in the new branch, as follows.
numbers.txt
, stage it, commit it.feature
branch will becomes part of that branch.master
ref and the HEAD
ref move to the new commit.As before, you can use the git log --oneline --decorate
command for this.
At times, the HEAD
ref of the local repo is represented as in Sourcetree, as illustrated in the screenshot below
.
The HEAD
ref is not shown in the UI if it is already pointing at the active branch.
numbers.txt
, stage the changes, and commit it. This commit too will be added to the feature1
branch.4 Switch to the master
branch. Note how the changes you made in the feature1
branch are no longer in the working directory.
$ git switch master
Double-click the master
branch.
Revisiting master
vs origin/master
In the screenshot above, you see a master
ref and a origin/master
ref for the same commit. The former identifies the of the local master
branch while the latter identifies the tip of the master
branch at the remote repo named origin
. The fact that both refs point to the same commit means the local master
branch and its remote counterpart are with each other.
Similarly, origin/HEAD
ref appearing against the same commit indicates that of the remote repo is pointing to this commit as well.
5 Add a commit to the master branch. Let’s imagine it’s a bug fix.
To keep things simple for the time being, this commit should not involve the numbers.txt
file that you changed in the feature1
branch. Of course, this is easily done, as the numbers.txt
file you added in the feature
branch is not even visible when you are in the master
branch.
gitGraph BT: %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "m1" commit id: "m2" branch feature1 commit id: "f1" commit id: "[feature1] f2" checkout master commit id: "[HEAD → master] m3" checkout feature1
6 Switch between the two branches and see how the working directory changes accordingly. That is, now you have two parallel timelines that you can freely switch between.
done!
You can also start a branch from an earlier commit, instead of the latest commit in the current branch. For that, simply check out the commit you wish to start from.
In the samplerepo-things
repo that you used above, let's create a new branch that starts from the same commit the feature1
branch started from. Let's pretend this branch will contain an alternative version of the content we added in the feature1
branch.
gitGraph BT: %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "m1" commit id: "m2" branch feature1 branch feature1-alt checkout feature1 commit id: "f1" commit id: "[feature1] f2" checkout master commit id: "[HEAD → master] m3" checkout feature1-alt commit id: "[HEAD → feature1-alt] a1"
Avoid this rookie mistake!
Always remember to switch back to the master
branch before creating a new branch. If not, your new branch will be created on top of the current branch.
master
branch.feature1
branch diverged from the master
branch (e.g. git checkout HEAD~1
). This will create a detached HEAD
.feature1-alt
. The HEAD
will now point to this new branch (i.e., no longer 'detached').PRO-TIP: Creating a branch based on another branch in one shot
Suppose you are currently on branch b2
and you want to create a new branch b3
that starts from b1
. Normally, you can do that in two steps:
git switch b1 # switch to the intended base branch first
git switch -c b3 # create the new branch and switch to it
This can be done in one shot using the git switch -c <new-branch> <base-branch>
command:
git switch -c b3 b1
done!
Most work done in branches eventually gets merged together.
Merging combines the changes from one branch into another, bringing their diverged timelines back together.
When you merge, Git looks at the two branches and figures out how their histories have diverged since their merge base (i.e., the most recent common ancestor commit of two branches). It then applies the changes from the other branch onto your current branch, creating a new commit. The new commit created when merging is called a merge commit — it records the result of combining both sets of changes.
Given below is an illustration of how such a merge looks like in the revision graph:
fix1
branch (as indicated by HEAD
).master
branch (thus, HEAD
is now pointing to master
ref).fix1
branch has been merged into the master
branch, creating a merge commit f
. The repo is still on the master
branch.A merge commit has two parent commits e.g., in the above example, the merge commit f
has both d
and e
as parent commits. The parent commit on the receiving branch is considered the first parent and the other is considered the second parent e.g., in the example above, fix1
branch is being merged into the master
branch (i.e., the receiving branch) -- accordingly, d
is the first parent and e
is the second parent.
Preparation We continue with the samplerepo-things
repo from earlier, which should look like the following. Note that we are ignoring the feature1-alt
branch, for simplicity.
gitGraph BT: %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "m1" commit id: "m2" branch feature1 commit id: "f1" commit id: "[feature1] f2" checkout master commit id: "[HEAD → master] m3" checkout feature1
1 Switch back to the feature1
branch.
gitGraph BT: %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "m1" commit id: "m2" branch feature1 commit id: "f1" commit id: "[HEAD → feature1] f2" checkout master commit id: "[master] m3" checkout feature1
2 Merge the master
branch to the feature1
branch, giving an end-result like the following. Also note how Git has created a merge commit (shown as mc1
in the diagram below).
gitGraph BT: %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "m1" commit id: "m2" branch feature1 commit id: "f1" commit id: "f2" checkout master commit id: "[master] m3" checkout feature1 merge master id: "[HEAD → feature1] mc1"
$ git merge master
Right-click on the master
branch and choose merge master into the current branch
. Click OK
in the next dialog.
The revision graph should look like this now (colours and line alignment might vary but the graph structure should be the same):
Observe how the changes you made in the master
branch (i.e., the imaginary bug fix in m3
) is now available even when you are in the feature1
branch.
Furthermore, observe (e.g., git show HEAD
) how the merge commit contains the sum of changes done in commits m3
, f1
, and f2
.
3 Add another commit to the feature1
branch, in which you do some further changes to the numbers.txt
.
Switch to the master
branch and add one more commit.
gitGraph BT: %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "m1" commit id: "m2" branch feature1 commit id: "f1" commit id: "f2" checkout master commit id: "m3" checkout feature1 merge master id: "mc1" commit id: "[feature1] f3" checkout master commit id: "[HEAD → master] m4"
4 Merge feature1
to the master branch, giving an end-result like this:
gitGraph BT: %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "m1" commit id: "m2" branch feature1 commit id: "f1" commit id: "f2" checkout master commit id: "m3" checkout feature1 merge master id: "mc1" commit id: "[feature1] f3" checkout master commit id: "m4" merge feature1 id: "[HEAD → master] mc2"
git merge feature1
Right-click on the feature1
branch and choose Merge...
. The resulting revision graph should look like this:
Now, any changes you made in feature1
branch are available in the master branch.
done!
When the branch you're merging into hasn't diverged — meaning it hasn't had any new commits since the merge base — Git simply moves the branch pointer forward to include all the new commits, keeping the history clean and linear. This is called a fast-forward merge because Git simply "fast-forwards" the branch pointer to the tip of the other branch. The result looks as if all the changes had been made directly on one branch, without any branching at all.
gitGraph BT: %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "m1" commit id: "[HEAD → master] m2" branch bug-fix commit id: "b1" commit id: "[bug-fix] b2" checkout master
→
[merge bug-fix
]
gitGraph BT: %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "m1" commit id: "m2" commit id: "b1" commit id: "[HEAD → master][bug-fix] b2" checkout master
In the example above, the master
branch has not changed since the merge base (i.e., m2
). Hence, merging the branch bug-fix
onto master
can be done by fast-forwarding the master
branch ref to the tip of the bug-fix
branch (i.e., b2
).
Preparation Let's continue with the same samplerepo-things
repo we used above, and do a fast-forward merge this time.
1 Create a new branch called add-countries
, and some commits to it as follows:
Switch to the new branch, add a file named countries.txt
, stage it, and commit it.
Do some changes to countries.txt
, and commit those changes.
You should have something like this now:
gitGraph BT: %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "[master] mc2" branch add-countries commit id: "a1" commit id: "[HEAD → add-countries] a2"
2 Go back to the master
branch.
gitGraph BT: %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "[HEAD → master] mc2" branch add-countries commit id: "a1" commit id: "add-countries] a2"
3 Merge the add-countries
branch onto the master
branch. Observe that there is no merge commit. The master
branch ref (and the HEAD
ref along with it) moved to the tip of the add-countries
branch (i.e., a2
) and both branches now point to a2
.
gitGraph BT: %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master (and add-countries)'}} }%% commit id: "mc2" commit id: "a1" commit id: "[HEAD → master][add-countries] a2"
done!
It is possible to force Git to create a merge commit even if fast forwarding is possible. This is useful if you prefer the revision graph to visually show when each branch was merged to the main timeline.
To prevent Git from fast-forwarding, use the --no-ff
switch when merging. Example:
git merge --no-ff add-countries
Windows: Tick the box shown below when you merge a branch:
Mac:
Trigger the branch operation using the following menu button:
In the next dialog, tick the following option:
To permanently prevent fast-forwarding:
Settings
.Git
section.Do not fast-forward when merging, always create commit
.A squash merge combines all the changes from a branch into a single commit on the receiving branch, without preserving the full commit history of the branch being merged. This is especially useful when the feature branch contains many small or experimental commits that would clutter the main branch’s history. By squashing, you retain the final state of the changes while presenting them as one cohesive unit, making the project history easier to read and manage. It also helps maintain a linear, simplified commit log on the main branch.
gitGraph BT: %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "[HEAD → master] m1" branch feature checkout feature commit id: "f1" commit id: "[feature] f2"
→
[squash merge...]
gitGraph BT: %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "m1" branch feature checkout feature commit id: "f1" commit id: "[feature] f2" checkout master commit id: "[HEAD → master] s1 (same as f1+f2)" type: HIGHLIGHT
In the example above, the branch feature
has been squash merged onto the master
branch, creating a single 'squashed' commit s1
that combines all the commits in feature
branch.
When merging branches, you need to guide Git on how to resolve conflicting changes in different branches.
A merge conflict happens when Git can't automatically combine changes from two branches because the same parts of a file were modified differently in each branch. When this happens, Git pauses the merge and marks the conflicting sections in the affected files so you can resolve them yourself. Once you've reviewed and fixed the conflicts, you can tell Git they're resolved and complete the merge.
More generally, a conflict occurs when Git cannot automatically reconcile different changes made to the same part of a file -- branch merge conflicts is just one example.
Target To simulate a merge conflict and use it to learn how to resolve merge conflicts.
Preparation You can use any repo with at least one commit in the master
branch.
1 Start a branch named fix1
in the repo. Create a commit that adds a line with some text to one of the files.
2 Switch back to master
branch. Create a commit with a conflicting change i.e., it adds a line with some different text in the exact location the previous line was added.
3 Try to merge the fix1
branch onto the master
branch. Git will pause mid-way during the merge and report a merge conflict. If you open the conflicted file, you will see something like this:
COLORS
------
blue
<<<<<< HEAD
black
=======
green
>>>>>> fix1
red
white
4 Observe how the conflicted part is marked between a line starting with <<<<<<
and a line starting with >>>>>>
, separated by another line starting with =======
.
Highlighted below is the conflicting part that is coming from the master
branch:
blue
<<<<<< HEAD
black
=======
green
>>>>>> fix1
red
This is the conflicting part that is coming from the fix1
branch:
blue
<<<<<< HEAD
black
=======
green
>>>>>> fix1
red
5 Resolve the conflict by editing the file. Let us assume you want to keep both lines in the merged version. You can modify the file to be like this:
COLORS
------
blue
black
green
red
white
6 Stage the changes, and commit. You have now successfully resolved the merge conflict.
done!
Branches can be renamed, for example, to fix a mistake in the branch name.
Local branches can be renamed easily. Renaming a branch simply changes the branch reference (i.e., the name used to identify the branch) — it is just a cosmetic change.
Preparation First, create the repo samplerepo-books
for this hands-on practical, by running the following commands in your terminal.
mkdir samplerepo-books
cd samplerepo-books
git init
echo "Horror Stories" >> horror.txt
git add .
git commit -m "Add horror.txt"
git switch -c textbooks
echo "Textbooks" >> textbooks.txt
git add .
git commit -m "Add textbooks.txt"
git switch master
git switch -c fantasy
echo "Fantasy Books" >> fantasy.txt
git add .
git commit -m "Add fantasy.txt"
git switch master
git merge --no-ff -m "Merge branch textbooks" textbooks
The above should give you a repo similar to the revision graph given below, on the left.
gitGraph BT: %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "m1" branch textbooks checkout textbooks commit id: "[textbooks] t1" checkout master branch fantasy checkout fantasy commit id: "[fantasy] f1" checkout master merge textbooks id: "[HEAD → master] mc1"
→
[rename branches]
gitGraph BT: %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "m1" branch study-books checkout study-books commit id: "[study-books] t1" checkout master branch fantasy-books checkout fantasy-books commit id: "[fantasy-books] f1" checkout master merge study-books id: "[HEAD → master] mc1"
Target Rename the fantasy
branch to fantasy-books
. Similarly, rename textbooks
branch to study-books
. The outcome should be similar to the revision graph above, on the right.
steps:
To rename a branch, use the git branch -m <current-name> <new-name>
command (-m
stands for 'move'):
git branch -m fantasy fantasy-books
git branch -m textbooks study-books
git log --oneline --decorate --graph --all # verify the changes
* 443132a (HEAD -> master) Merge branch textbooks
|\
| * 4969163 (study-books) Add textbooks.txt
|/
| * 0586ee1 (fantasy-books) Add fantasy.txt
|/
* 7f28f0e Add horror.txt
Note these additional switches to the log
command:
--all
: Shows all branches, not just the current branch.--graph
: Shows a graph-like visualisation (notice how *
is used to indicate a commit, and branches are indicated using vertical lines).Right-click on the branch name and choose Rename...
. Provide the new branch name in the next dialog.
done!
SIDEBAR: Branch naming conventions
Branch names can contain lowercase letters, numbers, /
, dashes (-
), underscores (_
), and dots (.
).
You can use uppercase letters too, but many teams avoid them for consistency.
A common branch naming convention is to prefix it with <category>/
. Some examples:
feature/login-form
— for new features (origin/feature/login-form
could be the matching remote-tracking branch)bugfix/profile-photo
— for fixing bugshotfix/payment-crash
— for urgent production fixesrelease/2.0
— for prepping a releaseexperiment/ai-chatbot
— for “just trying stuff”Although forward-slash (/
) in the prefix doesn't mean folders, some tools treat it kind of like a path so you can group related branches when you run git branch. Shown below is an example of how Sourcetree groups branches with the same prefix.
Branches can be deleted to get rid of them when they are no longer needed.
Deleting a branch deletes the corresponding branch ref from the revision history (it does not delete any commits). The impact of the loss of the branch ref depends on whether the branch has been merged.
When you delete a branch that has been merged, the commits of the branch will still exist in the history and will be safe. Only the branch ref is lost.
gitGraph BT: %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "m1" branch bug-fix checkout bug-fix commit id: "[bug-fix] b1" checkout master merge bug-fix id: "[HEAD → master] mc1"
→
[delete branch bug-fix
]
gitGraph BT: %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "m1" branch _ checkout _ commit id: "b1" checkout master merge _ id: "[HEAD → master] mc1"
In the above example, the only impact of the deletion is the loss of the branch ref bug-fix
. All commits remain reachable (via the master
branch), and there is no other impact on the revision history.
In fact, some prefer to delete the branch soon after merging it, to reduce branch references cluttering up the revision history.
When you delete a branch that has not been merged, the loss of the branch ref can render some commits unreachable (unless you know their commit IDs or they are reachable through other refs), putting them at risk of being lost eventually.
gitGraph BT: %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "[HEAD → master] m1" branch bug-fix checkout bug-fix commit id: "[bug-fix] b1" checkout master
→
[delete branch bug-fix
]
gitGraph BT: %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "[HEAD → master] m1" branch _ checkout _ commit id: "b1" checkout master
In the above example, the commit b1
is no longer reachable, unless we know its commit ID (i.e., the SHA
).
SIDEBAR: What makes a commit 'unreachable'?
Recall that a commit only has a pointer to its parent commit (not its descendent commits).
A commit is considered reachable if you can get to it by starting at a branch, tag, or other ref and walking backward through its parent commits. This is the normal state for commits — they are part of the visible history of a branch or tag.
When no branch, tag, or ref points to a commit (directly or indirectly), it becomes unreachable. This often happens when you delete a branch or rewrite history (e.g., with reset or rebase), leaving some commits "orphaned" (or "dangling") without a ref pointing to them.
In the example below, C4
is unreachable (i.e., cannot be reached by starting at any of the three refs: v1.0 or master or ←HEAD), but the other three are all reachable.
Unreachable commits are not deleted immediately — Git keeps them for a while before cleaning them up. By default, Git retains unreachable commits for at least 30 days, during which they can still be recovered if you know their SHA. After that, they will be garbage-collected, and will be lost for good.
Preparation First, create the repo samplerepo-books-2
for this hands-on practical, by running the following commands in your terminal.
mkdir samplerepo-books-2
cd samplerepo-books-2
git init
echo "Horror Stories" >> horror.txt
git add .
git commit -m "Add horror.txt"
git switch -c textbooks
echo "Textbooks" >> textbooks.txt
git add .
git commit -m "Add textbooks.txt"
git switch master
git switch -c fantasy
echo "Fantasy Books" >> fantasy.txt
git add .
git commit -m "Add fantasy.txt"
git switch master
git merge --no-ff -m "Merge branch textbooks" textbooks
1 Delete the (the merged) textbooks
branch.
Use the git branch -d <branch>
command to delete a local branch 'safely' -- this command will fail if the branch has unmerged changes.
git branch -d textbooks
git log --oneline --decorate --graph --all # check the current revision graph
* 443132a (HEAD -> master) Merge branch textbooks
|\
| * 4969163 Add textbooks.txt
|/
| * 0586ee1 (fantasy) Add fantasy.txt
|/
* 7f28f0e Add horror.txt
Right-click on the branch name and choose Delete <branch>
:
In the next dialog, click OK
:
Observe that all commits remain. The only missing thing is the textbook
ref.
2 Make a copy of the SHA
of the tip of the (unmerged) fantasy
branch.
3 Delete the fantasy
branch.
Attempt to delete the branch. It should fail, as shown below:
git branch -d fantasy
error: the branch 'fantasy' is not fully merged
hint: If you are sure you want to delete it, run 'git branch -D fantasy'
As also hinted by the error message, you can replace the -d
with -D
to 'force' the deletion.
git branch -D fantasy
Now, check the revision graph:
git log --oneline --decorate --graph --all
* 443132a (HEAD -> master) Merge branch textbooks
|\
| * 4969163 Add textbooks.txt
|/
* 7f28f0e Add horror.txt
Attempt to delete the branch as you did before. It will fail because the branch has unmerged commits.
Try again but this time, tick the Force delete
option, which will force Git to delete the unmerged branch:
Observe how the branch ref fantasy
is gone, together with any unmerged commits on it.
4 Attempt to view the 'unreachable' commit whose SHA
you noted in step 2.
e.g., git show 32b34fb
(use the SHA
you copied earlier)
Observe how the commit still exists and still is reachable using the commit ID, although it is not reachable by other means, and not visible in the revision graph.
done!
Merging is one way to keep one branch synchronised with another.
When working in parallel branches, you’ll often need to sync (short for synchronise) one branch with another. For example, while developing a feature in one branch, you might want to bring in a recent bug fix from another branch that your branch doesn’t yet have.
The simplest way to sync branches is to merge — that is, to sync a branch b1
with changes from another branch b2
, you merge b2
into b1
. In fact, you can merge them periodically to keep one branch up to date with the other.
gitGraph %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "m1" branch bug-fix branch feature commit id: "f1" checkout master checkout bug-fix commit id: "b1" checkout master merge bug-fix checkout feature merge master id: "mc1" commit id: "f2" checkout master commit id: "m2" checkout feature merge master id: "mc2" checkout master commit id: "m3" checkout feature commit id: "[feature] f3" checkout master commit id: "[HEAD → master] m4"
In the example above, you can see how the feature
branch is merging the master
branch periodically to keep itself in sync with the changes being introduced to the master
branch.
Rebasing is another way to synchronise one branch with another.
Rebasing is another way to synchronise one branch with another, while keeping the history cleaner and more linear. Instead of creating a merge commit to combine the branches, rebasing moves the entire sequence of commits from your branch and "replays" them on top of another branch. This effectively moves the base of your branch to the tip of the other branch (i.e., it 're-bases' it — hence the name), as if you had started your work from there in the first place.
Rebasing is especially useful when you want to update your branch with the latest changes from a main branch, but you prefer an uncluttered history with fewer merge commits.
Suppose we have the following revision graph, and we want to sync the feature
branch with master
, so that changes in commit m2
become visible to the feature
branch.
gitGraph %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "m1" branch feature checkout feature commit id: "f1" checkout master commit id: "[master] m2" checkout feature commit id: "[HEAD → feature] f2"
If we merge the master
branch to the feature
branch as given below, m2
becomes visible to the feature
branch. However, it creates a merge commit.
gitGraph %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "m1" branch feature checkout feature commit id: "f1" checkout master commit id: "[master] m2" checkout feature commit id: "f2" merge master id: "[HEAD → feature] mc1"
Instead of merging, if we rebased the feature
branch on the master
branch, we would get the following.
gitGraph %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "m1" checkout master commit id: "[branch: master] m2" branch feature checkout feature commit id: "f1a" commit id: "[HEAD → feature] f2a"
Note how the rebasing changed the base of the feature
branch from m1
to m2
. As a result, changes done in m2
are now visible to the feature
branch. But there is no merge commit, and the revision graph is simpler.
Also note how the first commit in the feature branch, previously shown as f1
, is now shown as f1a
after the rebase. Although both commits contain the same changes, other details -- such as the parent commit -- are different, making them two distinct Git objects with different SHA values. Similarly, f2
and f2a
are also different. Thus, the history of the entire feature
branch has changed after the rebase.
Because rebasing rewrites the commit history of your branch, you should avoid rebasing branches that you’ve already published, and are potentially used by others -- rewriting published history can cause confusion and conflicts for those using the previous version of the commits.
Cherry-picking is a Git operation that copies over a specific commit from one branch to another.
Cherry-picking is another way to synchronise branches, by applying specific commits from one branch onto another.
Unlike merging or rebasing — which bring over all changes since the branches diverged — cherry-picking lets you choose individual commits and apply just those, one at a time, to your current branch. This is useful when you want to bring over a bug fix or a small feature from another branch without merging the entire branch history.
Because cherry-picking copies only the chosen commits, it creates new commits on your branch with the same changes but different SHA values.
Suppose we have the following revision graph, and we want to bring over the changes introduced in m3
(in the master
branch) onto the feature
branch.
gitGraph %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "m1" branch feature checkout feature commit id: "f1" checkout master commit id: "m2" commit id: "m3" type: HIGHLIGHT commit id: "[master] m4" checkout feature commit id: "[HEAD → feature] f2"
After cherry-picking m3
onto the feature
branch, the revision graph should look like the following:
gitGraph %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "m1" branch feature checkout feature commit id: "f1" checkout master commit id: "m2" commit id: "m3" type: HIGHLIGHT commit id: "[master] m4" checkout feature commit id: "f3" commit id: "[HEAD → feature] m3a" type: HIGHLIGHT
Note how it makes the changes done in m3
available (from now on) in the feature
branch, with minimal changes to the revision graph. Also note that the new commit m3a
contains the same changes as m3
, but it will be a different Git object with a different SHA value.
Cherry-picking is another Git operation that can result in conflicts i.e., if the changes in the cherry-picked commit conflict with the changes in the receiving branch.
Local branches can be replicated in a remote.
Pushing a copy of local branches to the corresponding remote repo makes those branches available remotely.
In a previous lesson, we saw how to push the default branch to a remote repository and have Git set up tracking between the local and remote branches using a remote-tracking reference. Pushing any other local branch to a remote works the same way as pushing the default branch — you simply specify the target branch instead of the default branch. Pushing any new commits in any local branch to a corresponding remote branch is done similarly as well.
gitGraph BT: %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "m1" branch bug-fix checkout master commit id: "[origin/master][HEAD → master] m2" checkout bug-fix commit id: "[bug-fix] b1" checkout master
[bug-fix
branch does not exist in the remote origin
]
→
gitGraph BT: %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "m1" branch bug-fix checkout master commit id: "[origin/master][HEAD → master] m2" checkout bug-fix commit id: "[origin/bug-fix][bug-fix] b1" checkout master
[after pushing bug-fix
branch to origin,
and setting up a remote-tracking branch]
Preparation Fork the samplerepo-company to your GitHub account. When doing so, un-tick the Copy the master branch only
option.
After forking, go to the fork and ensure both branches (master
, and track-sales
) are in there.
Clone the fork to your computer. It should look something like this:
gitGraph BT: %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "m1" commit id: "m2" branch track-sales checkout track-sales commit id: "[origin/track-sales] s1" checkout master commit id: "[origin/master][origin/HEAD][HEAD → master] m3"
The origin/HEAD
remote-tracking ref indicates where the HEAD
ref is in the remote origin
.
1 Create a new branch called hiring
, and add a commit to that branch. The commit can contain any changes you want.
Here are the commands you can run in the terminal to do this step in one shot:
git switch -c hiring
echo "Receptionist: Pam" >> employees.txt
git commit -am "Add Pam to employees.txt"
gitGraph BT: %%{init: { 'theme': 'default', 'gitGraph': {'mainBranchName': 'master'}} }%% commit id: "m1" commit id: "m2" branch track-sales checkout track-sales commit id: "[origin/track-sales] s1" checkout master commit id: "[origin/master][origin/HEAD][master] m3" branch hiring checkout hiring commit id: "[HEAD → hiring] h1"
The resulting revision graph should look like the one above.
2 Push the hiring
branch to the remote.
You can use the usual git push <remote> -u <branch>
command to push the branch to the remote, and set up a remote-tracking branch at the same time.
git push origin -u hiring
3 Verify that the branch has been pushed to the remote by visiting the fork on GitHub, and looking for the origin/hiring
remote-tracking ref in the local repo.
done!
Branches in a remote can be replicated in the local repo, and maintained in sync with each other.
Sometimes we need to create a local copy of a branch from a remote repository, make further changes to it, and keep it synchronised with the remote branch. Let's explore how to handle this in a few common use cases:
Use case 1: Working with branches that already existed in the remote repo when you cloned it to your computer.
When you clone a repository,
Preparation Use the same samplerepo-company repo you used in Lesson T8L1. Pushing Branches to a Remote. Fork and clone it if you haven't done that already.
1 Verify that the remote-tracking branch origin/track-sales
exists in the local repo, but there is no local copy of it.
You can use the git branch -a
command to list all local and tracking branches.
git branch -a
* hiring
master
remotes/origin/HEAD -> origin/master
remotes/origin/hiring
remotes/origin/master
remotes/origin/track-sales
The *
in the output above indicates the currently active branch.
Note how there is no track-sales
in the list of branches (i.e., no local branch named track-sales
), but there is a remotes/origin/track-sales
(i.e., the remote-tracking branch)
Observe how the branch track-sales
appear under REMOTES
→ origin
but not under BRANCHES
.
2 Create a local copy of the remote branch origin/track-sales
.
You can use the git switch -c <branch> <remote-branch>
command for this e.g.,
git switch -c track-sales origin/track-sales
Locate the track-sales
remote-tracking branch (look under REMOTES
→ origin
), right-click, and choose Checkout...
.
In the next dialog, choose as follows:
The above command/action does several things:
track-sales
.origin/track-sales
, which means the local branch ref track-sales
will also move to where the origin/track-sales
is.3 Add a commit to the track-sales
branch and push to the remote, to verify that the local branch is tracking the remote branch.
Commands to perform this step in one shot:
echo "5 reams of paper" >> sales.txt
git commit -am "Update sales.txt"
git push origin track-sales
done!
Use case 2: Working with branches that were added to the remote repository after you cloned it e.g., a branch someone else pushed to the remote after you cloned.
Simply fetch to update your local repository with information about the new branch. After that, you can create a local copy of it and work with it just as you did in Use Case 1.
Fetching was covered in Lesson T3L3. Downloading Data Into a Local Repo.
Often, you'll need to delete a branch in a remote repo after it has served its purpose.
To delete a branch in a remote repository, you simply tell Git to remove the reference to that branch from the remote. This does not delete the branch from your local repository — it only removes it from the remote, so others won’t see it anymore. This is useful for cleaning up clutter in the remote repo e.g., delete old or merged branches that are no longer needed on the remote.
Preparation Fork the samplerepo-books to your GitHub account. When doing so, un-tick the Copy the master branch only
option.
After forking, go to the fork and ensure all three branches are in there.
Clone the fork to your computer.
1 Create a local copy of the fantasy
branch in your clone.
Follow instructions in Lesson T8L2. Pulling Branches from a Remote.
2 Delete the remote branch fantasy
.
You can use the git push <remote> --delete <branch>
command to delete a branch in a remote. This is like pushing changes in a branch to a remote, except we request the branch to be deleted instead, by adding the --delete
switch.
git push origin --delete fantasy
Locate the remote branch under REMOTES
→ origin
, right-click on the branch name, and choose Delete...
:
3 Verify that the branch was deleted from the remote, by going to the fork on GitHub and checking the branches page https://github.com/{YOUR_USERNAME}/samplerepo-books/branches
e.g., https://github.com/johndoe/samplerepo-books/branches
.
Also verify that the local copy has not been deleted.
4 Restore the remote branch from the local copy.
Push the local branch to the remote, while enabling the tracking option (as if pushing the branch to the remote for the first time), as covered in Lesson T8L1. Pushing Branches to a Remote.
In the above steps, we first created a local copy of the branch before deleting it in the remote repo. Doing so is optional. You can delete a remote branch without ever checking it out locally — you just need to know its name on the remote. Deleting the remote branch directly without creating a local copy is recommended if you simply want to clean up a remote branch you no longer need.
done!
Occasionally, you might need to rename a branch in a remote repo.
Git does not have a way to rename remote branches in place. Instead, you create a new branch with the desired name and delete the old one. This involves renaming your local branch to the new name, pushing it to the remote (which effectively creates a new remote branch), and then removing the old branch from the remote. This ensures the remote reflects the updated name while preserving the commit history and any work already done on the branch.
While Git cannot rename a remote branch in place, GitHub allows you to rename a branch in a remote repo. If you use this approach, the local repo still needs to be updated to reflect the change.
Preparation You can use the fork and the clone of the samplerepo-books that you created in Lesson T8L3. Deleting Branches from a Remote.
Target Rename the branch fantasy
in the remote (i.e., your fork) to fantasy-books
.
Steps
master
branch.origin/fantasy
.fantasy-books
.git switch master # ensure you are on the master branch
git switch -c fantasy origin/fantasy # create a local copy, tracking the remote branch
git branch -m fantasy fantasy-books # rename local branch
git push -u origin fantasy-books # push the new branch to remote, and set it to track
git push origin --delete fantasy # delete the old branch
You can run the git log --oneline --decorate --graph --all
to check the revision graph after each step. The final outcome should be something like the below:
* 355915c (HEAD -> fantasy-books, origin/fantasy-books) Add fantasy.txt
| * 027b2b0 (origin/master, origin/HEAD, master) Merge branch textbooks
|/|
| * a6ebaec (origin/textbooks) Add textbooks.txt
|/
* d462638 Add horror.txt
Perform the above steps (each step was covered in a previous lesson).
done!
A pull request (PR for short) is a mechanism for contributing code to a remote repo i.e., "I'm requesting you to pull my proposed changes to your repo". It's feature provided by RCS platforms such as GitHub. For this to work, the two repos must have a shared history. The most common case is sending PRs from a fork to its repo.
Suppose you want to propose some changes to a GitHub repo (e.g., samplerepo-pr-practice) as a pull request (PR).
samplerepo-pr-practice is an unmonitored repo you can use to practice working with PRs. Feel free to send PRs to it.
Given below is a scenario you can try in order to learn how to create PRs:
1. Fork the repo onto your GitHub account.
2. Clone it onto your computer.
3. Commit your changes e.g., add a new file with some contents and commit it.
master
branchadd-intro
(remember to switch to the master
branch before creating a new branch) and add your commit to it.4. Push the branch you updated (i.e., master
branch or the new branch) to your fork, as explained here.
5. Initiate the PR creation:
Go to your fork.
Click on the Pull requests tab followed by the New pull request button. This will bring you to the Compare changes
page.
Set the appropriate target repo and the branch that should receive your PR, using the base repository
and base
dropdowns. e.g.,
base repository: se-edu/samplerepo-pr-practice base: master
Normally, the default value shown in the dropdown is what you want but in case your fork has , the default may not be what you want.
Indicate which repo:branch contains your proposed code, using the head repository
and compare
dropdowns. e.g.,
head repository: myrepo/samplerepo-pr-practice compare: master
6. Verify the proposed code: Verify that the diff view in the page shows the exact change you intend to propose. If it doesn't, as necessary.
7. Submit the PR:
Click the Create pull request button.
Fill in the PR name and description e.g.,
Name: Add an introduction to the README.md
Description:
Add some paragraph to the README.md to explain ...
Also add a heading ...
If you want to indicate that the PR you are about to create is 'still work in progress, not yet ready', click on the dropdown arrow in the Create pull request button and choose Create draft pull request
option.
Click the Create pull request button to create the PR.
Go to the receiving repo to verify that your PR appears there in the Pull requests
tab.
The next step of the PR lifecycle is the PR review. The members of the repo that received your PR can now review your proposed changes.
You can update the PR along the way too. Suppose PR reviewers suggested a certain improvement to your proposed code. To update your PR as per the suggestion, you can simply modify the code in your local repo, commit the updated code to the same branch as before, and push to your fork as you did earlier. The PR will auto-update accordingly.
Sending PRs using the master
branch is less common than sending PRs using separate branches. For example, suppose you wanted to propose two bug fixes that are not related to each other. In that case, it is more appropriate to send two separate PRs so that each fix can be reviewed, refined, and merged independently. But if you send PRs using the master
branch only, both fixes (and any other change you do in the master
branch) will appear in the PRs you create from it.
To create another PR while the current PR is still under review, create a new branch (remember to switch back to the master
branch first), add your new proposed change in that branch, and create a new PR following the steps given above.
It is possible to create PRs within the same repo e.g., you can create a PR from branch feature-x
to the master
branch, within the same repo. Doing so will allow the code to be reviewed by other developers (using PR review mechanism) before it is merged.
Problem: merge conflicts in ongoing PRs, indicated by the message This branch has conflicts that must be resolved. That means the upstream repo's master
branch has been updated in a way that the PR code conflicts with that master
branch. Here is the standard way to fix this problem:
master
branch from the upstream repo to your local repo.git checkout master
git pull upstream master
master
branch (that you updated in the previous step) onto the PR branch, in order to bring over the new code in the master
branch to your PR branch.git checkout pr-branch # assuming pr-branch is the name of branch in the PR
git merge master
master
branch.
Resolve the conflict manually (this topic is covered elsewhere), and complete the merge.master
branch, the merge conflict alert in the PR will go away automatically.The PR review stage is a dialog between the PR author and members of the repo that received the PR, in order to refine and eventually merge the PR.
Given below are some steps you can follow when reviewing a PR.
1. Locate the PR:
2. Read the PR description. It might contain information relevant to reviewing the PR.
3. Click on the Files changed tab to see the diff view.
You can use the following setting to try the two different views available and pick the one you like.
4. Add review comments:
suggestion
code block generated by GitHub (as seen in the screenshot above).5. Submit the review:
Overall, I found your code easy to read for the most part except a few places
where the nesting was too deep. I noted a few minor coding standard violations
too. Some of the classes are getting quite long. Consider splitting into
smaller classes if that makes sense.
LGTM
is often used in such overall comments, to indicate Looks good to me
(or Looks good to merge
).nit
(as in nit-picking) is another such term, used to indicate minor flaws e.g., LGTM. Just a few nits to fix.
.Approve
, Comment
, or Request changes
option as appropriate and click on the Submit review button.Let's look at the steps involved in merging a PR, assuming the PR has been reviewed, refined, and approved for merging already.
Preparation: If you would like to try merging a PR yourself, you can create a dummy PR in the following manner.
feature1
) and add some commits to it.master
branch in your fork. Yes, it is possible to create a PR within the same repo.1. Locate the PR to be merged in your repo's GitHub page.
2. Click on the Conversation tab and scroll to the bottom. You'll see a panel containing the PR status summary.
3. If the PR is not merge-able in the current state, the Merge pull request will not be green. Here are the possible reasons and remedies:
master
branch has been updated since the PR code was last updated.
master
branch has been updated since the PR code was last updated, in a way that the PR code conflicts with the current master
branch. Those conflicts must be resolved before the PR can be merged.
4. Merge the PR by clicking on the Merge pull request button, followed by the Confirm merge
button. You should see a Pull request successfully merged and closed
message after the PR is merged.
Create merge commit
option is recommended.Next, sync your local repos (and forks). Merging a PR simply merges the code in the upstream remote repository in which it was merged. The PR author (and other members of the repo) needs to pull the merged code from the upstream repo to their local repos and push the new code to their respective forks to sync the fork with the upstream repo.
RCS can be done in two ways: the centralized way and the distributed way.
Centralized RCS (CRCS for short) uses a central remote repo that is shared by the team. Team members interact directly with this central repository. Older RCS tools such as CVS and SVN support only this model.
The centralized RCS approach without any local repos (e.g., CVS, SVN)
Distributed RCS (DRCS for short, also known as Decentralized RCS) allows multiple remote/local repos working together. The workflow can vary from team to team. For example, every team member can have his/her own remote repository in addition to their own local repository, as shown in the diagram below. Git and Mercurial are some prominent RCS tools that support the distributed approach.
The decentralized RCS approach
In the forking workflow, the 'official' version of the software is kept in a remote repo designated as the 'main repo'. All team members fork the main repo and create pull requests from their fork to the main repo.
To illustrate how the workflow goes, let’s assume Jean wants to fix a bug in the code. Here are the steps:
master
branch -- if Jean does that, she will not be able to have more than one PR open at any time because any changes to the master
branch will be reflected in all open PRs.master
branch to each of them.One main benefit of this workflow is that it does not require most contributors to have write permissions to the main repository. Only those who are merging PRs need write permissions. The main drawback of this workflow is the extra overhead of sending everything through forks.
You can follow the steps in the simulation of a forking workflow given below to learn how to follow such a workflow.
This activity is best done as a team.
Step 1. One member: set up the team org and the team repo.
Create a GitHub organization for your team, if you don't have one already. The org name is up to you. We'll refer to this organization as team org from now on.
Add a team called developers
to your team org.
Add team members to the developers
team.
Fork se-edu/samplerepo-workflow-practice to your team org. We'll refer to this as the team repo.
Add the forked repo to the developers
team. Give write access.
Step 2. Each team member: create PRs via own fork.
Fork that repo from your team org to your own GitHub account.
Create a branch named add-{your name}-info
(e.g. add-johnTan-info
) in the local repo.
Add a file yourName.md
into the members
directory (e.g., members/johnTan.md
) containing some info about you into that branch.
Push that branch to your fork.
Create a PR from that branch to the master
branch of the team repo.
Step 3. For each PR: review, update, and merge.
[A team member (not the PR author)] Review the PR by adding comments (can be just dummy comments).
[PR author] Update the PR by pushing more commits to it, to simulate updating the PR based on review comments.
[Another team member] Approve and merge the PR using the GitHub interface.
[All members] Sync your local repo (and your fork) with upstream repo. In this case, your upstream repo is the repo in your team org.
master
branch to each of them.Step 4. Create conflicting PRs.
[One member]: Update README: In the master
branch, remove John Doe and Jane Doe from the README.md
, commit, and push to the main repo.
[Each team member] Create a PR to add yourself under the Team Members
section in the README.md
. Use a new branch for the PR e.g., add-johnTan-name
.
Step 5. Merge conflicting PRs one at a time. Before merging a PR, you’ll have to resolve conflicts.
[Optional] A member can inform the PR author (by posting a comment) that there is a conflict in the PR.
[PR author] Resolve the conflict locally:
master
branch from the repo in your team org.master
branch to your PR branch.[Another member or the PR author]: Merge the de-conflicted PR: When GitHub does not indicate a conflict anymore, you can go ahead and merge the PR.
Feature branch workflow is similar to forking workflow except there are no forks. Everyone is pushing/pulling from the same remote repo. The phrase feature branch is used because each new feature (or bug fix, or any other modification) is done in a separate branch and merged to the master
branch when ready. Pull requests can still be created within the central repository, from the feature branch to the main branch.
As this workflow require all team members to have write access to the repository,
Software development goes through different stages such as requirements, analysis, design, implementation and testing. These stages are collectively known as the software development lifecycle (SDLC). There are several approaches, known as software development lifecycle models (also called software process models), that describe different ways to go through the SDLC. Each process model prescribes a 'roadmap' for the software developers to manage the development effort. The roadmap describes the aims of the development stages, the outcome of each stage, and the workflow i.e., the relationship between stages.
The sequential model, also called the waterfall model, views software development as a linear process, in which the project is seen as progressing through the development stages. The name waterfall stems from how the model is drawn to look like a waterfall (see below).
When one stage of the process is completed, it produces some artifacts to be used in the next stage. For example, the requirements stage produces a comprehensive list of requirements, to be used in the design phase.
A strict sequential model project moves only in the forward direction i.e., each stage is completed before starting the next. For example, once the requirements stage is over, there is no provision for revising the requirements later.
This model can work well for a project that produces software to solve a well-understood problem, in which case the requirements can remain stable and the effort can be estimated accurately. Furthermore, as each stage has a well-defined outcome, it is easy to track the progress of the project because one can gauge the project progress by monitoring which stage the project is in.
However, real-world projects often tackle problems that are not well-understood at the beginning, making them unsuitable for this model. For example, target users of a software product may not be able to state their requirements accurately at the start of the project, if they have not used a similar product before.
The iterative model advocates producing the software by going through several iterations. Each of the iterations could potentially go through all the stages of the SDLC, from requirements gathering to deployment.
Each iteration produces a new version of the product, building upon the version produced in the previous iteration. Feedback from each iteration is factored into the subsequent iterations. For example, if an implementation task took longer than expected, the effort estimate for a similar tasks in future iterations can be adjusted accordingly. Similarly, if a feature introduced in the current iteration was not well-received by target users, it can be removed or tweaked in the next iteration.
The iterative model can be done in breadth-first or depth-first approach.
Taking a Minesweeper game as an example,
A project can be done as a mixture of breadth-first and depth-first iterations i.e., an iteration can contain some breadth-first work as well as some depth-first work, or, some iterations can be breadth-first while others are depth-first.
In 2001, a group of prominent software engineering practitioners met and brainstormed for an alternative to documentation-driven, heavyweight software development processes that were used in most large projects at the time. This resulted in something called the agile manifesto (a vision statement of what they were looking to do).
You are uncovering better ways of developing software by doing it and helping others do it.
Through this work you have come to value:
- Individuals and interactions over processes and tools
- Working software over comprehensive documentation
- Customer collaboration over contract negotiation
- Responding to change over following a plan
That is, while there is value in the items on the right, you value the items on the left more.
-- Extract from the Agile Manifesto
Subsequently, some of the signatories of the manifesto went on to create process models that try to follow it. These processes are collectively called agile processes. Some of the key features of agile approaches are:
There are a number of agile processes in the development world today. eXtreme Programming (XP) and Scrum are two of the well-known ones.
The following description was adapted from the XP home page, emphasis added:
Extreme Programming (XP) stresses customer satisfaction. Instead of delivering everything you could possibly want on some date far in the future, this process delivers the software you need as you need it.
XP aims to empower developers to confidently respond to changing customer requirements, even late in the lifecycle.
XP emphasizes teamwork. Managers, customers, and developers are all equal partners in a collaborative team. XP implements a simple, yet effective environment enabling teams to become highly productive. The team self-organizes around the problem to solve it as efficiently as possible.
XP aims to improve a software project in five essential ways: communication, simplicity, feedback, respect, and courage. Extreme Programmers constantly communicate with their customers and fellow programmers. They keep their design simple and clean. They get feedback by testing their software starting on day one. Every small success deepens their respect for the unique contributions of each and every team member. With this foundation, Extreme Programmers are able to courageously respond to changing requirements and technology.
XP has a set of simple rules. XP is a lot like a jig saw puzzle with many small pieces. Individually the pieces make no sense, but when combined together a complete picture can be seen. This flow chart shows how Extreme Programming's rules work together.
Pair programming, CRC cards, project velocity, and standup meetings are some interesting topics related to XP. Refer to www.extremeprogramming.org to find out more about XP.
This description of Scrum was adapted from Wikipedia [retrieved on 18/10/2011], emphasis added:
Scrum is a process skeleton that contains sets of practices and predefined roles. The main roles in Scrum are:
A Scrum project is divided into iterations called Sprints. A sprint is the basic unit of development in Scrum. Sprints tend to last between one week and one month, and are a timeboxed (i.e., restricted to a specific duration) effort of a constant length.
Each sprint is preceded by a planning meeting, where the tasks for the sprint are identified and an estimated commitment for the sprint goal is made, and followed by a review or retrospective meeting, where the progress is reviewed and lessons for the next sprint are identified.
During each sprint, the team creates a potentially deliverable product increment (for example, working and tested software). The set of features that go into a sprint come from the product backlog, which is a prioritized set of high level requirements of work to be done. Which backlog items go into the sprint is determined during the sprint planning meeting. During this meeting, the Product Owner informs the team of the items in the product backlog that he or she wants completed. The team then determines how much of this they can commit to complete during the next sprint, and records this in the sprint backlog. During a sprint, no one is allowed to change the sprint backlog, which means that the requirements are frozen for that sprint. Development is timeboxed such that the sprint must end on time; if requirements are not completed for any reason they are left out and returned to the product backlog. After a sprint is completed, the team demonstrates the use of the software.
Scrum enables the creation of self-organizing teams by encouraging co-location of all team members, and verbal communication between all team members and disciplines in the project.
A key principle of Scrum is its recognition that during a project the customers can change their minds about what they want and need (often called requirements churn), and that unpredicted challenges cannot be easily addressed in a traditional predictive or planned manner. As such, Scrum adopts an empirical approach—accepting that the problem cannot be fully understood or defined, focusing instead on maximizing the team’s ability to deliver quickly and respond to emerging requirements.
Daily Scrum is another key scrum practice. The description below was adapted from https://www.mountaingoatsoftware.com (emphasis added):
In Scrum, on each day of a sprint, the team holds a daily scrum meeting called the "daily scrum.” Meetings are typically held in the same location and at the same time each day. Ideally, a daily scrum meeting is held in the morning, as it helps set the context for the coming day's work. These scrum meetings are strictly time-boxed to 15 minutes. This keeps the discussion brisk but relevant.
...
During the daily scrum, each team member answers the following three questions:
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The daily scrum meeting is not used as a problem-solving or issue resolution meeting. Issues that are raised are taken offline and usually dealt with by the relevant subgroup immediately after the meeting.
A Work Breakdown Structure (WBS) depicts information about tasks and their details in terms of subtasks. When managing projects, it is useful to divide the total work into smaller, well-defined units. Relatively complex tasks can be further split into subtasks. In complex projects, a WBS can also include prerequisite tasks and effort estimates for each task.
The high level tasks for a single iteration of a small project could look like the following:
Task ID | Task | Estimated Effort | Prerequisite Task |
---|---|---|---|
A | Analysis | 1 man day | - |
B | Design | 2 man day | A |
C | Implementation | 4.5 man day | B |
D | Testing | 1 man day | C |
E | Planning for next version | 1 man day | D |
The effort is traditionally measured in man hour/day/month i.e., work that can be done by one person in one hour/day/month. The Task ID is a label for easy reference to a task. Simple labeling is suitable for a small project, while a more informative labeling system can be adopted for bigger projects.
An example WBS for a game development project.
Task ID | Task | Estimated Effort | Prerequisite Task |
---|---|---|---|
A | High level design | 1 man day | - |
B |
Detail design
|
2 man day
| A |
C |
Implementation
|
4.5 man day
|
|
D | System Testing | 1 man day | C |
E | Planning for next version | 1 man day | D |
All tasks should be well-defined. In particular, it should be clear as to when the task will be considered done.
Some examples of ill-defined tasks and their better-defined counterparts:
Bad | Better |
---|---|
more coding | implement component X |
do research on UI testing | find a suitable tool for testing the UI |
A milestone is the end of a stage which indicates significant progress. You should take into account dependencies and priorities when deciding on the features to be delivered at a certain milestone.
Each intermediate product release is a milestone.
In some projects, it is not practical to have a very detailed plan for the whole project due to the uncertainty and unavailability of required information. In such cases, you can use a high-level plan for the whole project and a detailed plan for the next few milestones.
Milestones for the Minesweeper project, iteration 1
Day | Milestones |
---|---|
Day 1 | Architecture skeleton completed |
Day 3 | ‘new game’ feature implemented |
Day 4 | ‘new game’ feature tested |
A buffer is time set aside to absorb any unforeseen delays. It is very important to include buffers in a software project schedule because effort/time estimations for software development are notoriously hard. However, do not inflate task estimates to create hidden buffers; have explicit buffers instead. Reason: With explicit buffers, it is easier to detect incorrect effort estimates which can serve as feedback to improve future effort estimates.
Keeping track of project tasks (who is doing what, which tasks are ongoing, which tasks are done etc.) is an essential part of project management. In small projects, it may be possible to keep track of tasks using simple tools such as online spreadsheets or general-purpose/light-weight task tracking tools such as Trello. Bigger projects need more sophisticated task tracking tools.
Issue trackers (sometimes called bug trackers) are commonly used to track task assignment and progress. Most online project management software such as GitHub, SourceForge, and BitBucket come with an integrated issue tracker.
A screenshot from the Jira Issue tracker software (Jira is part of the BitBucket project management tool suite):
A Gantt chart is a 2-D bar-chart, drawn as time vs tasks (represented by horizontal bars).
A sample Gantt chart:
In a Gantt chart, a solid bar represents the main task, which is generally composed of a number of subtasks, shown as grey bars. The diamond shape indicates an important deadline/deliverable/milestone.
Given below are three commonly used team structures in software development. Irrespective of the team structure, it is a good practice to assign roles and responsibilities to different team members so that someone is clearly in charge of each aspect of the project. In comparison, the ‘everybody is responsible for everything’ approach can result in more chaos and hence slower progress.
Egoless team
In this structure, every team member is equal in terms of responsibility and accountability. When any decision is required, consensus must be reached. This team structure is also known as a democratic team structure. This team structure usually finds a good solution to a relatively hard problem as all team members contribute ideas.
However, the democratic nature of the team structure bears a higher risk of falling apart due to the absence of an authority figure to manage the team and resolve conflicts.
Chief programmer team
Frederick Brooks proposed that software engineers learn from the medical surgical team in an operating room. In such a team, there is always a chief surgeon, assisted by experts in other areas. Similarly, in a chief programmer team structure, there is a single authoritative figure, the chief programmer. Major decisions, e.g., system architecture, are made solely by him/her and obeyed by all other team members. The chief programmer directs and coordinates the effort of other team members. When necessary, the chief will be assisted by domain specialists e.g., business specialists, database experts, network technology experts, etc. This allows individual group members to concentrate solely on the areas in which they have sound knowledge and expertise.
The success of such a team structure relies heavily on the chief programmer. Not only must he/she be a superb technical hand, he/she also needs good managerial skills. Under a suitably qualified leader, such a team structure is known to produce successful work.
Strict hierarchy team
At the opposite extreme of an egoless team, a strict hierarchy team has a strictly defined organization among the team members, reminiscent of the military or a bureaucratic government. Each team member only works on his/her assigned tasks and reports to a single “boss”.
In a large, resource-intensive, complex project, this could be a good team structure to reduce communication overhead.
Single responsibility principle (SRP): A class should have one, and only one, reason to change. -- Robert C. Martin
If a class has only one responsibility, it needs to change only when there is a change to that responsibility.
Consider a TextUi
class that does parsing of the user commands as well as interacting with the user. That class needs to change when the formatting of the UI changes as well as when the syntax of the user command changes. Hence, such a class does not follow the SRP.
Gather together the things that change for the same reasons. Separate those things that change for different reasons. ―- Agile Software Development, Principles, Patterns, and Practices by Robert C. Martin
The Open-Closed Principle aims to make a code entity easy to adapt and reuse without needing to modify the code entity itself.
Open-closed principle (OCP): A module should be open for extension but closed for modification. That is, modules should be written so that they can be extended, without requiring them to be modified. -- proposed by Bertrand Meyer
In object-oriented programming, OCP can be achieved in various ways. This often requires separating the specification (i.e., interface) of a module from its implementation.
In the design given below, the behavior of the CommandQueue
class can be altered by adding more concrete Command
subclasses. For example, by including a Delete
class alongside List
, Sort
, and Reset
, the CommandQueue
can now perform delete commands without modifying its code at all. That is, its behavior was extended without having to modify its code. Hence, it is open to extensions, but closed to modification.
The behavior of a Java generic class can be altered by passing it a different class as a parameter. In the code below, the ArrayList
class behaves as a container of Students
in one instance and as a container of Admin
objects in the other instance, without having to change its code. That is, the behavior of the ArrayList
class is extended without modifying its code.
ArrayList students = new ArrayList<Student>();
ArrayList admins = new ArrayList<Admin>();
Liskov substitution principle (LSP): Derived classes must be substitutable for their base classes. -- proposed by Barbara Liskov
LSP sounds the same as substitutability but it goes beyond substitutability; LSP implies that a subclass should not be more restrictive than the behavior specified by the superclass. As you know, Java has language support for substitutability. However, if LSP is not followed, substituting a subclass object for a superclass object can break the functionality of the code.
Suppose the Payroll
class depends on the adjustMySalary(int percent)
method of the Staff
class. Furthermore, the Staff
class states that the adjustMySalary
method will work for all positive percent values. Both the Admin
and Academic
classes override the adjustMySalary
method.
Now consider the following:
Admin#adjustMySalary
method works for both negative and positive percent values.Academic#adjustMySalary
method works for percent values 1..100
only.In the above scenario,
Admin
class follows LSP because it fulfills Payroll
’s expectation of Staff
objects (i.e., it works for all positive values). Substituting Admin
objects for Staff
objects will not break the Payroll
class functionality.Academic
class violates LSP because it will not work for percent values over 100
as expected by the Payroll
class. Substituting Academic
objects for Staff
objects can potentially break the Payroll
class functionality.The five OOP principles given below are known as SOLID Principles (an acronym made up of the first letter of each principle):
Separation of concerns principle (SoC): To achieve better modularity, separate the code into distinct sections, such that each section addresses a separate concern. -- Proposed by Edsger W. Dijkstra
A concern in this context is a set of information that affects the code of a computer program.
Examples for concerns:
add employee
featurepersistence
or security
Employee
entityApplying reduces functional overlaps among code sections and also limits the ripple effect when changes are introduced to a specific part of the system.
If the code related to persistence is separated from the code related to security, a change to how the data are persisted will not need changes to how the security is implemented.
This principle can be applied at the class level, as well as at higher levels.
The n-tier architecture utilizes this principle. Each layer in the architecture has a well-defined functionality that has no functional overlap with each other.
This principle should lead to higher cohesion and lower coupling.
Law of Demeter (LoD):
Also known as
More concretely, a method m
of an object O
should invoke only the methods of the following kinds of objects:
O
itselfm
m
(directly or indirectly) The following code fragment violates LoD due to the following reason: while b
is a ‘friend’ of foo
(because it receives it as a parameter), g
is a ‘friend of a friend’ (which should be considered a ‘stranger’), and g.doSomething()
is analogous to ‘talking to a stranger’.
void foo(Bar b) {
Goo g = b.getGoo();
g.doSomething();
}
LoD aims to prevent objects from navigating the internal structures of other objects.
An analogy for LoD can be drawn from Facebook. If Facebook followed LoD, you would not be allowed to see posts of friends of friends, unless they are your friends as well. If Jake is your friend and Adam is Jake’s friend, you should not be allowed to see Adam’s posts unless Adam is a friend of yours as well.