The following description of the Joys of the Programming Craft was taken 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, we want others to use our 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 we 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....

[Text and book cover source: Wikipedia]	[Fred Brooks photo source]

The Mythical Man-Month: Essays on Software Engineering is a book on software engineering and project management by Fred Brooks, whose central theme is that "adding manpower to a late software project makes it later". This idea is known as Brooks's law, and is presented along with the second-system effect and advocacy of prototyping.

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 we 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.

_{-- Object-Oriented Programming with Objective-C, Apple}

Some other examples of programming paradigms are:

Some programming languages support multiple paradigms.

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.

_{-- Object-Oriented Programming with Objective-C, Apple}

Object Oriented Programming (OOP) views the world as a network of interacting objects.

OOP solutions try to create a similar object network inside the computer’s memory – a sort of a 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.

Every object has both state (data) and behavior (operations on data).

Every object has an interface and an implementation.

Every real world object has:

• an interface through which other objects can interact with it
• an implementation that supports the interface but may not be accessible to the other object

Similarly, every object in the virtual world has an interface and an implementation.

Objects interact by sending messages. Both real world and virtual world object interactions can be viewed as objects sending message 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).

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.

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 uses to,

1. create the virtual world of of the object network, and
2. provide it the inputs to produce the outcome we want.

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 one kind (or ‘class’) of objects can be done once and that same instructions can be used to instantiate objects of that kind. We call such instructions a Class.

While all objects of a class has the same attributes, each object has its own copy of the attribute value.

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.

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.

However, there can be methods related to a specific class but not suitable for sending message 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.

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.

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.

Associations in an object structure can change over time.

Associations among objects can be generalized as associations between the corresponding classes too.

Implementing associations

We use instance level variables to implement associations.

When two classes are linked by an association, it does not necessarily mean both classes know about each other. The concept of which class in the association knows about the other class is called navigability.

Multiplicity is the aspect of an OOP solution that dictates how many objects take part in each association.

Implementing multiplicity

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.

class Logic{
    Minefield minefield;
}

class Minefield{
    ...
}

class Logic:
  
  def __init__(self, minefield):
    self.minefield = minefield
    
  # ...


class Minefield:
  # ...

A variable can be used to implement a 1 multiplicity too (also called compulsory associations).

class Logic {
    ConfigGenerator cg = new ConfigGenerator();
    ...
}

class Logic:

  def __init__(self):
    self.config_gen = ConfigGenerator()

Bi-directional associations require matching variables in both classes.

class Foo {
    Bar bar;
    //...
}

class Bar {
    Foo foo;
    //...
}

class Foo:
  
  def __init__(self, bar):
    self.bar = bar;


class Bar:
  
  def __init__(self, foo):
    self.foo = foo;
    

To implement other multiplicities, choose a suitable data structure such as Arrays, ArrayLists, HashMaps, Sets, etc.

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 direction association with it. One cause of dependencies is interactions between objects that do not have a long-term link between them.

Implementing dependencies

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. When the whole is destroyed, parts are destroyed too.

Composition also implies that there cannot be cyclical links.

Implementing composition

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.

class Email {
    private Subject subject;
  ...
}

class Email:

  def __init__(self):
    self.__subject = Subject()

Aggregation represents a container-contained relationship. It is a weaker relationship than composition.

Implementing aggregation

Implementation is similar to that of composition except the containee object can exist even after the container object is deleted.

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

The OOP concept Inheritance allows you to define a new class based on an existing class.

• Other names for Base class: Parent class, Super class
• Other names for Derived class: Child class, Sub class, Extended class

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.

Inheritance implies the derived class can be considered as a sub-type 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 sub-type relationship exists. However, the two often go hand-in-hand. For simplicity, at this point let us assume inheritance implies a sub-type relationship.

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 an Vehicle, an Asset and a Liability.

Method overriding is when a sub-class changes the behavior inherited from the parent class by re-implementing the method. Overridden methods have the same name, same type signature, and same return type.

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.

An interface is a behavior specification i.e. a collection of method specifications. If a class implements the interface, 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}

A class implementing an interface results in an is-a relationship, just like in class inheritance.

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.

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 Academic is an instance of a Staff, but a Staff is not necessarily an instance of an Academic. 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

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.

Polymorphism literally means "ability to take many forms".

What’s the difference between a Class, an Abstract Class, and an Interface?

• An interface is a behavior specification with no implementation.
• A class is a behavior specification + implementation.
• An abstract class is a behavior specification + a possibly incomplete implementation.

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,

• a brown-field project i.e., develop a product to replace/update an existing software product
• a green-field project i.e., develop a totally new system with no precedent

In either case, requirements need to be gathered, analyzed, specified, and managed.

Requirements come from stakeholders.

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:

1. Functional requirements specify what the system should do.
2. Non-functional requirements specify the constraints under which system is developed and operated.

We may have to spend an extra effort in digging NFRs out as early as possible because,

1. NFRs are easier to miss e.g., stakeholders tend to think of functional requirements first
2. sometimes NFRs are critical to the success of the software. E.g. A web application that is too slow or that has low security is unlikely to succeed even if it has all the right functionality.

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 that project requirements.

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.

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.

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.

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.

Avoid using lengthy prose to describe requirements; they can be hard to follow.

A common format for writing user stories is:

We can write user stories on index cards or sticky notes, and arrange on walls or tables, to facilitate planning and discussion. Alternatively, we can use a software (e.g., GitHub Project Boards, Trello, Google Docs, ...) to manage user stories digitally.

^{[credit: https://www.flickr.com/photos/jakuza/2682466984/]}

^{[credit: https://www.flickr.com/photos/jakuza/with/2726048607/]}

^{[credit: https://commons.wikimedia.org/wiki/File:User_Story_Map_in_Action.png]}

The {benefit} can be omitted if it is obvious.

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.

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’.

Other useful info that can be added to a user story includes (but not limited to)

• Priority: how important the user story is
• Size: the estimated effort to implement the user story
• Urgency: how soon the feature is needed

User stories capture user requirements in a way that is convenient for scoping, estimation, and scheduling.

[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 traditional requirements specifications 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.

While use cases can be recorded on physical paper in the initial stages, an online tool is more suitable for longer-term management of user stories, especially if the team is not co-located.

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 below, 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 supplementary requirements section can be used to capture requirements that do not fit elsewhere. Typically, this is where most Non Functional Requirements will be listed.

Software design has two main aspects:

• Product/external design: designing the external behavior of the product to meet the users' requirements. This is usually done by product designers with the input from business analysts, user experience experts, user representatives, etc.
• Implementation/internal design: designing how the product will be implemented to meet the required external behavior. This is usually done by software architects and software engineers.

The guiding principle of abstraction is that only details that are relevant to the current perspective or the task at hand needs 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

Control abstraction: abstracting away details of the actual control flow to focus on tasks at a higher level

Abstraction can be applied repeatedly to obtain progressively higher levels of abstractions.

Abstraction is a general concept that is not limited to just data or control abstractions.

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:

• Maintenance is harder because a change in one module could cause changes in other modules coupled to it (i.e. a ripple effect).
• Integration is harder because multiple components coupled with each other have to be integrated at the same time.
• Testing and reuse of the module is harder due to its dependence on other modules.

In the example below, design A appears to have a 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.

class Foo{
    ...
    new Bar().read();
    ...
}

class Bar{
    void read(){
        ...
    }
    
    void write(){
        ...
    }
}

Cohesion 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):

• Lowers the understandability of modules as it is difficult to express module functionalities at a higher level.
• Lowers maintainability because a module can be modified due to unrelated causes (reason: the module contains code unrelated to each other) or many many modules may need to be modified to achieve a small change in behavior (reason: because the code realated to that change is not localized to a single module).
• Lowers reusability of modules because they do not represent logical units of functionality.

Cohesion can be present in many forms. Some examples:

• Code related to a single concept is kept together, e.g. the Student component handles everything related to students.
• Code that is invoked close together in time is kept together, e.g. all code related to initializing the system is kept together.
• Code that manipulates the same data structure is kept together, e.g. the GameArchive component handles everything related to the storage and retrieval of game sessions.

A model is a representation of something else.

A class diagram is a diagram drawn using the UML modelling notation.
An example class diagram:

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.

Multiple models of the same entity may be needed to capture it fully.

In software development, models are useful in several ways:

a) To analyze a complex entity related to software development.

b) To communicate information among stakeholders. Models can be used as a visual aid in discussions and documentations.

c) As a blueprint for creating software. Models can be used as instructions for building software.

The following diagram uses the class diagram notation to show the different types of UML diagrams.

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.

Note that these object structures within the same software can change over time.

However, object structures do not change at random; they change based on a set of rules, as was decided 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.

UML Object Diagrams are used to model object structures and UML Class Diagrams are used to model class structures of an OO solution.

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:

UML notes can be used to add more info to any UML model.

A class diagram can also show different types of associations: 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.

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:

• A source code editor that includes features such as syntax coloring, auto-completion, easy code navigation, error highlighting, and code-snippet generation.
• A compiler and/or an interpreter (together with other build automation support) that facilitates the compilation/linking/running/deployment of a program.
• A debugger that allows the developer to execute the program one step at a time to observe the run-time behavior in order to locate bugs.
• Other tools that aid various aspects of coding e.g. support for automated testing, drag-and-drop construction of UI components, version management support, simulation of the target runtime platform, and modeling support.

Examples of popular IDEs:

• Java: Eclipse, Intellij IDEA, NetBeans
• C#, C++: Visual Studio
• Swift: XCode
• Python: PyCharm

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:

• Bad -- By inserting temporary print statements: This is an ad-hoc approach in which print statements are inserted in the program to print information relevant to debugging, such as variable values. e.g. Exiting process() method, x is 5.347. This approach is not recommended due to these reasons.
  • Incurs extra effort when inserting and removing the print statements.
  • These extraneous program modifications increases the risk of introducing errors into the program.
  • These print statements, if not removed promptly after the debugging, may even appear unexpectedly in the production version.
• Bad -- By manually tracing through the code: Otherwise known as ‘eye-balling’, this approach doesn't have the cons of the previous approach, but it too is not recommended (other than as a 'quick try') due to these reasons:
  • It is difficult, time consuming, and error-prone technique.
  • If you didn't spot the error while writing code, you might not spot the error when reading code too.
• Good -- Using a debugger: A debugger tool allows you to pause the execution, then step through one statement at a time while examining the internal state if necessary. Most IDEs come with an inbuilt debugger. This is the recommended approach for debugging.

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 of software, poor quality code is something we cannot 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 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 we do not intend to pass the code to someone else, code quality is still important because we all become 'strangers' to our own code someday.

int subsidy() {
    int subsidy;
    if (!age) {
        if (!sub) {
            if (!notFullTime) {
                subsidy = 500;
            } else {
                subsidy = 250;
            }
        } else {
            subsidy = 250;
        }
    } else {
        subsidy = -1;
    }
    return subsidy;
}

int calculateSubsidy() {
    int subsidy;
    if (isSenior) {
        subsidy = REJECT_SENIOR;
    } else if (isAlreadySubsidised) {
        subsidy = SUBSIDISED_SUBSIDY;
    } else if (isPartTime) {
        subsidy = FULLTIME_SUBSIDY * RATIO;
    } else {
        subsidy = FULLTIME_SUBSIDY;
    }
    return subsidy;
}

def calculate_subs():
    if not age:
        if not sub:
            if not not_fulltime:
                subsidy = 500
            else:
                subsidy = 250
        else:
            subsidy = 250
    else:
        subsidy = -1
    return subsidy

def calculate_subsidy():
    if is_senior:
        return REJECT_SENIOR
    elif is_already_subsidised:
        return SUBSIDISED_SUBSIDY
    elif is_parttime:
        return FULLTIME_SUBSIDY * RATIO
    else:
        return FULLTIME_SUBSIDY

Be wary when a method is longer than the computer screen, and take corrective action when it goes beyond 30 LOC (lines of code). 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 CodingStyle}

In particular, avoid arrowhead style code.

int subsidy() {
    int subsidy;
    if (!age) {
        if (!sub) {
            if (!notFullTime) {
                subsidy = 500;
            } else {
                subsidy = 250;
            }
        } else {
            subsidy = 250;
        }
    } else {
        subsidy = -1;
    }
    return subsidy;
}

int calculateSubsidy() {
    int subsidy;
    if (isSenior) {
        subsidy = REJECT_SENIOR;
    } else if (isAlreadySubsidised) {
        subsidy = SUBSIDISED_SUBSIDY;
    } else if (isPartTime) {
        subsidy = FULLTIME_SUBSIDY * RATIO;
    } else {
        subsidy = FULLTIME_SUBSIDY;
    }
    return subsidy;
}

def calculate_subs():
    if not age:
        if not sub:
            if not not_fulltime:
                subsidy = 500
            else:
                subsidy = 250
        else:
            subsidy = 250
    else:
        subsidy = -1
    return subsidy

def calculate_subsidy():
    if is_senior:
        return REJECT_SENIOR
    elif is_already_subsidised:
        return SUBSIDISED_SUBSIDY
    elif is_parttime:
        return FULLTIME_SUBSIDY * RATIO
    else:
        return FULLTIME_SUBSIDY

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).

return ((length < MAX_LENGTH) || (previousSize != length)) && (typeCode == URGENT);

boolean isWithinSizeLimit = length < MAX_LENGTH;
boolean isSameSize = previousSize != length;
boolean isValidCode = isWithinSizeLimit || isSameSize;

boolean isUrgent = typeCode == URGENT;

return isValidCode && isUrgent;

return ((length < MAX_LENGTH) or (previous_size != length)) and (type_code == URGENT)

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}

When the code has a number that does not explain the meaning of the number, we call that a "magic number" (as in "the number appears as if by magic"). Using a named constant makes the code easier to understand because the name tells us more about the meaning of the number.

return 3.14236;
...
return 9;

static final double PI = 3.14236;
static final int MAX_SIZE = 10;
...
return PI;
...
return MAX_SIZE-1;

return 3.14236
...
return 9

PI = 3.14236
MAX_SIZE = 10
...
return PI
...
return MAX_SIZE-1

Similarly, we can have ‘magic’ values of other data types.

"Error 1432"  // A magic string!

In general, try to avoid any magic literals.

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 grouping 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 we 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 group related statements together. 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.

One essential way to improve code quality is to follow a consistent style. That is why software engineers follow a strict coding standard (aka style guide).

The aim of a coding standard is to make the entire code base look like it was written by one person. A coding standard is usually specific to a programming language and specifies guidelines such as the location 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 use the same coding standard and that standard is not generally inconsistent with typical industry practices. If a company's coding standards is very different from what is used typically 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.

Proper naming improves the readability. It also reduces bugs caused by ambiguities regarding the intent of a variable or a method.

There are only two hard things in Computer Science: cache invalidation and naming things. _{-- Phil Karlton}

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.

Distinguish clearly between single-valued and multivalued variables.

Person student;
ArrayList<Person> students;

name = 'Jim'
names = ['Jim', 'Alice']

Use correct spelling in names. Avoid 'texting-style' spelling. Avoid foreign language words, slang, and names that are only meaningful within specific contexts/times e.g. terms from private jokes, a TV show currently popular in your country

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'. This is not so. Avoid writing comments to explain bad code. Improve the code to make it self-explanatory.

If the code is self-explanatory, refrain from repeating the description in a comment just for the sake of 'good documentation'.

// increment x
x++;

//trim the input
trimInput();

// increment x
x = x + 1

//trim the input
trim_input()

Do not write comments as if they are private notes to yourself. Instead, write them well enough to be understood by another programmer. One type of comments that is almost always useful is the header comment that you write for a class or an operation to explain its purpose.

// a quick trim function used to fix bug I detected overnight
void trimInput(){
    ....
}

/** Trims the input of leading and trailing spaces */
void trimInput(){
    ....
}

# a quick trim function used to fix bug I detected overnight
def trim_input():
    ...

def trim_input():
"""Trim the input of leading and trailing spaces"""
    ...

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. This process of improving a program's internal structure in small steps without modifying its external behavior is called refactoring.

• Refactoring is not rewriting: Discarding poorly-written code entirely and re-writing it from scratch is not refactoring because refactoring needs to be done in small steps.
• Refactoring is not bug fixing: By definition, refactoring is different from bug fixing or any other modifications that alter the external behavior (e.g. adding a feature) of the component in concern.

Given below are two common refactorings (more).

if (isSpecialDeal()) {
    total = price * 0.95;
    send();
} else {
    total = price * 0.98;
    send();
}

if (isSpecialDeal()){
    total = price * 0.95;
} else {
    total = price * 0.98;
}
send();

if is_special_deal:
    total = price * 0.95
    send()
else:
    total = price * 0.98
    send()

if is_special_deal:
    total = price * 0.95
else:
    total = price * 0.98
    
send()

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 built in 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.

Given below are some more commonly used refactorings. A more comprehensive list is available at refactoring-catalog .

1. Consolidate Conditional Expression
2. Decompose Conditional
3. Inline Method
4. Remove Double Negative
5. Replace Magic Literal
6. Replace Nested Conditional with Guard Clauses
7. Replace Parameter with Explicit Methods
8. Reverse Conditional
9. Split Loop
10. Split Temporary Variable

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 run time.

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.

Advantages of exception handling in this way:

• The ability to propagate error information through the call stack.
• The separation of code that deals with 'unusual' situations from the code that does the 'usual' work.

In general, use exceptions only for 'unusual' conditions. Use normal return statements to pass control to the caller for conditions that are 'normal'.

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.

If the runtime detects an assertion failure, it typically take 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.

int timeout = Config.getTimeout(); 

Use the assert keyword to define assertions.

x = getX();
assert x == 0 : "x should be 0";
...

Assertions can be disabled without modifying the code.

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: They are similar in purpose but JUnit assertions are more powerful and customized for testing. In addition, JUnit assertions are not disabled by default. We recommend you 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 considered 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.

...
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.

• The raising of an exception indicates an unusual condition created by the user (e.g. user inputs an unacceptable input) or the environment (e.g., a file needed for the program is missing).
• An assertion failure indicates the programmer made a mistake in the code (e.g., a null value is returned from a method that is not supposed to return null under any circumstances).

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 action can then be taken to prevent it from happening again.

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/platform 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:

• The reused code may be an overkill (think using a sledgehammer to crack a nut) increasing the size of, or/and degrading the performance of, your software.
• The reused software may not be mature/stable enough to be used in an important product. That means the software can change drastically and rapidly, possibly in ways that break your software.
• Non-mature software has the risk of dying off as fast as they emerged, leaving you with a dependency that is no longer maintained.
• The license of the reused software (or its dependencies) restrict how you can use/develop your software.
• The reused software might have bugs, missing features, or security vulnerabilities that are important to your product but not so important to the maintainers of that software, which means those flaws will not get fixed as fast as you need them to.
• Malicious code can sneak into your product via compromised dependencies.

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.

When developing large systems, if you define the API of each components 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.

These are the typical steps required to use a library.

1. Read the documentation to confirm that its functionality fits your needs
2. Check the license to confirm that it allows reuse in the way you plan to reuse it. For example, some libraries might allow non-commercial use only.
3. Download the library and make it accessible to your project. Alternatively, you can configure your dependency management tool to do it for you.
4. Call the library API from your code where you need to use the library functionality.

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.

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.

Some frameworks provide a complete implementation of a default behavior which makes them immediately usable.

A framework facilitates the adaptation and customization of some desired functionality.

Some frameworks cover only a specific components or an aspect.

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.

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:

1. Validation: are we building the right system i.e., are the requirements correct?
2. Verification: are we building the system right i.e., are the requirements implemented correctly?

Whether something belongs under validation or verification is not that important. What is more important is both are done, instead of limiting to verification (i.e., remember that the requirements can be wrong too).

Code review is the systematic examination 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

  • Project Management Platforms such as GitHub and BitBucket allow the new code to be proposed as Pull Requests and provide the ability for others to review the code in the PR.

• In pair programming

  • As pair programming involves two programmers working on the same code at the same time, there is an implicit review of the code by the other member of the pair.

• Formal inspections

  • Inspections involve a group of people systematically examining a project artifacts to discover defects. Members of the inspection team play various roles during the process, such as:

    • the author - the creator of the artifact
    • the moderator - the planner and executor of the inspection meeting
    • the secretary - the recorder of the findings of the inspection
    • the inspector/reviewer - the one who inspects/reviews the artifact.

Advantages of code reviews over testing:

• It can detect functionality defects as well as other problems such as coding standard violations.
• Can verify non-code artifacts and incomplete code
• Do not require test drivers or stubs.

Disadvantages:

• It is a manual process and therefore, error prone.

Static analysis of code can find useful information such 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.

Higher-end static analyzer tools can perform more complex analysis such as locating potential bugs, memory leaks, inefficient code structures etc.

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:

• Formal verification can be used to prove the absence of errors. In contrast, testing can only prove the presence of error, not their absence.

Disadvantages:

• It only proves the compliance with the specification, but not the actual utility of the software.
• It requires highly specialized notations and knowledge which makes it an expensive technique to administer. Therefore, formal verifications are more commonly used in safety-critical software such as flight control systems.

When testing, we 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.

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 we do the following:

1. Feed the input to the SUT
2. Observe the actual output
3. Compare actual output with the expected output

A test case failure is a mismatch between the expected behavior and the actual behavior. A failure indicates a potential defect (or a bug), unless the error is in the test case itself.

In OOP code, it is common to write one or more unit tests for each public method of a class.

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(sefl):
      # a unit test for read() method
  
  def test_write_emptyIntput_ignored(self):
      # a unit tests for write(string) method
  
  def test_write_normalInput_writtenCorrectly(self):
      # another unit tests for write(string) method

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 of what the parts are supposed to do vs what the parts are actually doing.

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' having pushed beyond its limits.

Test case: load a web page that is too big
* Input: load a web page containing more than 5000 characters. 
* Expected behavior: abort the loading of the page and show a meaningful error message. 

System testing includes testing against non-functional requirements too. Here are some examples.

• Performance testing – to ensure the system responds quickly.
• Load testing (also called stress testing or scalability testing) – to ensure the system can work under heavy load.
• Security testing – to test how secure the system is.
• Compatibility testing, interoperability testing – to check whether the system can work with other systems.
• Usability testing – to test how easy it is to use the system.
• Portability testing – to test whether the system works on different platforms.

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.

Developer testing is the testing done by the developers themselves as opposed to professional testers or end-users.

Delaying testing until the full product is complete has a number of disadvantages:

• Locating the cause of such a test case failure is difficult due to a large search space; in a large system, the search space could be millions of lines of code, written by hundreds of developers! The failure may also be due to multiple inter-related bugs.
• Fixing a bug found during such testing could result in major rework, especially if the bug originated during the design or during requirements specification i.e. a faulty design or faulty requirements.
• One bug might 'hide' other bugs, which could emerge only after the first bug is fixed.
• The delivery may have to be delayed if too many bugs were found during testing.

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 of partially developed software is usually, and by necessity, done by the developers themselves i.e. developer testing.

Here are two alternative approaches to testing a software: Scripted testing and Exploratory testing

1. 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.

2. 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.

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 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:

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

Passing system tests does not necessarily mean passing acceptance testing. Some examples:

• The system might work on the testbed environments but might not work the same way in the deployment environment, due to subtle differences between the two environments.
• The system might conform to the system specification but could fail to solve the problem it was supposed to solve for the user, due to flaws in the system design.

When we 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. Note that to detect regressions, we need to retest 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.

A simple way to semi-automate testing of a CLI(Command Line Interface) app is by using input/output re-direction.

• First, we feed the app with a sequence of test inputs that is stored in a file while redirecting the output to another file.
• Next, we compare the actual output file with another file containing the expected output.

Let us assume we are testing a CLI app called AddressBook. Here are the detailed steps:

1. Store the test input in the text file input.txt.

   add Valid Name p/12345 valid@email.butNoPrefix
   add Valid Name 12345 e/valid@email.butPhonePrefixMissing
   

2. Store the output we expect from the SUT in another text file expected.txt.

   Command: || [add Valid Name p/12345 valid@email.butNoPrefix]
   Invalid command format: add 
   
   Command: || [add Valid Name 12345 e/valid@email.butPhonePrefixMissing]
   Invalid command format: add 
   

3. 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 code changes to AddressBook.

   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 command window to run the app, not a Power Shell window.

   More on the > operator and the < operator extra

   A CLI program takes input from the keyboard and outputs to the console. That is because those two are default input and output streams, respectively. But you can change that behavior using < and > operators. For example, if you run AddressBook in a command window, the output will be shown in the console, but if you run it like this,

   java AddressBook > output.txt 
   

   the Operating System then creates a file output.txt and stores the output in that file instead of displaying it in the console. No file I/O coding is required. Similarly, adding < input.txt (or any other filename) makes the OS redirect the contents of the file as input to the program, as if the user typed the content of the file one line at a time.

   Resources:

   • Using command redirection operators in Windows

4. Next, we compare output.txt with the expected.txt. This can be done using a utility such as Windows FC (i.e. File Compare) command, Unix 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 we need more sophisticated ways of automating tests.

A test driver is the code that ‘drives’ the SUT for the purpose of testing i.e. invoking the SUT with test inputs and verifying the behavior is as expected.

public class PayrollTestDriver {
    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.

@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 has integrated support for testing tools. The figure below shows the JUnit output when running some JUnit tests using the Eclipse IDE.

Revision control software are also known as Version Control Software (VCS), and by a few other names.

Tracking and Ignoring

In a repo, we can specify which files to track and which files to ignore. Some files such as temporary log files created during the build/test process should not be revision-controlled.

Staging and Committing

Identifying Points in History

Each commit in a repo is a recorded point in the history of the project that is uniquely identified by an auto-generated hash e.g. a16043703f28e5b3dab95915f5c5e5bf4fdc5fc1.

We can tag a specific commit with a more easily identifiable name e.g. v1.0.2

RCS tools store the history of the working directory as a series of commits. This means we should commit after each change that we want the RCS to 'remember' for us.

To see what changed between two points of the history, you can ask the RCS tool to diff the two commits in concern.

To restore the state of the working directory at a point in the past, you can checkout the commit in concern. i.e., we can traverse the history of the working directory simply by checking out the commits we are interested in.

Remote repositories are copies of a repo that are hosted on remote computers. They are especially useful for sharing the revision history of a codebase among team members of a multi-person project. They can also serve as a remote backup of your code base.

You can clone a remote repo onto your computer which will create a copy of a remote repo on your computer, including the version history as the remote repo.

You can push new commits in your clone to the remote repo which will copy the new commits onto the remote repo. Note that pushing to a remote repo requires you to have write-access to it.

You can pull from the remote repos to receive new commits in the remote repo. Pulling is used to sync your local repo with latest changes to the remote repo.

While it is possible to set up your own remote repo on a server, an easier option is to use a remote repo hosting service such as GitHub or BitBucket.

A fork is a remote copy of a remote repo. If there is a remote repo that you want to push to but you do not have write access to it, you can fork the remote repo, which gives you your own remote repo that you can push to.

A pull request is mechanism for contributing code to a remote repo. It is a formal request sent to the maintainers of the repo asking them to pull your new code to their repo.

Branching is the process of evolving multiple versions of the software in parallel. For example, one team member can create a new branch and add an experimental feature to it while the rest of the team keeps working on another branch. Branches can be given names e.g. master, release, dev.

A branch can be merged into another branch. Merging usually result in a new commit that represents the changes done in the branch being merged.

Merge conflicts happen when you try to merge two branches that had changed the same part of the code and the RCS software cannot decide which changes to keep. In those cases we have to ‘resolve’ those conflicts manually.

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 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.

All tasks should be well-defined. In particular, it should be clear as to when the task will be considered done.

A milestone is the end of a stage which indicates a significant progress. We should take into account dependencies and priorities when deciding on the features to be delivered at a certain 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, we can use a high-level plan for the whole project and a detailed plan for the next few milestones.

A buffer is a 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 is 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 a 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 track tasks using simple tools as online spreadsheets or general-purpose/light-weight tasks 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):

If a class has only one responsibility, it needs to change only when there is a change to that responsibility.

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}

A concern in this context is a set of information that affects the code of a computer program.

Applying SoC reduces functional overlaps among code sections and also limits the ripple effect when changes are introduced to a specific part of the system.

This principle can be applied at the class level, as well as on higher levels.

Design → Architecture → Styles → n-Tier Style →

What

In the n-tier style, higher layers make use of services provided by lower layers. Lower layers are independent of higher layers. Other names: multi-layered, layered.

Operating systems and network communication software often use n-tier style.

This principle should lead to higher cohesion and lower coupling.

Design → Design Fundamentals → Coupling →

What

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:

• Maintenance is harder because a change in one module could cause changes in other modules coupled to it (i.e. a ripple effect).
• Integration is harder because multiple components coupled with each other have to be integrated at the same time.
• Testing and reuse of the module is harder due to its dependence on other modules.

In the example below, design A appears to have a more coupling between the components than design B.

Discuss the coupling levels of alternative designs x and y.

Overall coupling levels in x and y seem to be similar (neither has more dependencies than the other). (Note that the number of dependency links is not a definitive measure of the level of coupling. Some links may be stronger than the others.). However, in x, A is highly-coupled to the rest of the system while B, C, D, and E are standalone (do not depend on anything else). In y, no component is as highly-coupled as A of x. However, only D and E are standalone.

Explain the link (if any) between regressions and coupling.

When the system is highly-coupled, the risk of regressions is higher too e.g. when component A is modified, all components ‘coupled’ to component A risk ‘unintended behavioral changes’.

Discuss the relationship between coupling and testability.

Coupling decreases testability because if the SUT is coupled to many other components it becomes difficult to test the SUI in isolation of its dependencies.

Choose the correct statements.

• a. As coupling increases, testability decreases.
• b. As coupling increases, the risk of regression increases.
• c. As coupling increases, the value of automated regression testing increases.
• d. As coupling increases, integration becomes easier as everything is connected together.
• e. As coupling increases, maintainability decreases.

(a)(b)(c)(d)(e)

Explanation: High coupling means either more components require to be integrated at once in a big-bang fashion (increasing the risk of things going wrong) or more drivers and stubs are required when integrating incrementally.

UML class diagrams describe the structure (but not the behavior) of an OOP solution. These are possibly the most often used diagrams in the industry and an indispensable tool for an OO programmer.

An example class diagram:

The basic UML notations used to represent a class:

A Table class shown in UML notation:

class Table{

    Integer number;
    Chair[] chairs = null;
    
    Integer getNumber(){
        //...
    }

    void setNumber(Integer n){
        //...
    }
}

class Table:

  def __init__(self):
    self.number = 0
    self.chairs = []

  def get_number(self):
    # ...

  def set_number(self, n):
    # ...

The 'Operations' compartment and/or the 'Attributes' compartment may be omitted if such details are not important for the task at hand. 'Attributes' always appear above the 'Operations' compartment. All operations should be in one compartment rather than each operation in a separate compartment. Same goes for attributes.

The visibility of attributes and operations is used to indicate the level of access allowed for each attribute or operation. The types of visibility and their exact meanings depend on the programming language used. Here are some common visibilities and how they are indicated in a class diagram:

• + : public
• - : private
• # : protected
• ~ : package private

Table class with visibilities shown:

We use a solid line to show an association between two classes.

We use arrow heads to indication the navigability of an association.

Logic is aware of Minefield, but Minefield is not aware of Logic

class Logic{
    Minefield minefield;
}

class Minefield{
    ...
}

class Logic:
  
  def __init__(self, minefield):
    self.minefield = minefield
    
  # ...


class Minefield:
  # ...

Here is an example of a bidirectional navigability; each class is aware of the other.

Navigability can be shown in class diagrams as well as object diagrams.

According to this object diagram the given Logic object is associated with and aware of two MineField objects.

Association Role labels are used to indicate the role played by the classes in the association.

This association represents a marriage between a Man object and a Woman object. The respective roles played by objects of these two classes are husband and wife.

Note how the variable names match closely with the association roles.

class Man{
    Woman wife;
}

class Woman{
    Man husband;
}

class Man:
  def __init__(self):
    self.wife = None # a Woman object

class Woman:
   def __init__(self):
     self.husband = None # a Man object

The role of Student objects in this association is charges (i.e. Admin is in charge of students)

class Admin{
    List<Student> charges;
}

class Admin:
  def __init__(self):
    self.charges = [] # list of Student objects

Association labels describe the meaning of the association. The arrow head indicates the direction in which the label is to be read.

In this example, the same association is described using two different labels.

• Diagram on the left: Admin class is associated with Student class because an Admin object uses a Student object.
• Diagram on the right: Admin class is associated with Student class because a Student object is used by an Admin object.

Commonly used multiplicities:

• 0..1 : optional, can be linked to 0 or 1 objects
• 1 : compulsory, must be linked to one object at all times.
• * : can be linked to 0 or more objects.
• n..m : the number of linked objects must be n to m inclusive

In the diagram below, an Admin object administers (in charge of) any number of students but a Student object must always be under the charge of exactly one Admin object

In the diagram below,

• Each student must be supervised by exactly one professor. i.e. There cannot be a student who doesn't have a supervisor or has multiple supervisors.
• A professor cannot supervise more than 5 students but can have no students to supervise.
• An admin can handle any number of professors and any number of students, including none.
• A professor/student can be handled by any number of admins, including none.

UML uses a dashed arrow to show dependencies.

Two examples of dependencies:

Notation:

In the class diagram below, there are two enumerations in use:

In UML class diagrams, underlines denote class-level attributes and variables.

In the class below, totalStudents attribute and the getTotalStudents method are class-level.

UML uses a solid diamond symbol to denote composition.

Notation:

A Book consists of Chapter objects. When the Book object is destroyed, its Chapter objects are destroyed too.

UML uses a hollow diamond is used to indicate an aggregation.

Notation:

Example:

You can use a triangle and a solid line (not to be confused with an arrow) to indicate class inheritance.

Notation:

Examples: The Car class inherits from the Vehicle class. The Cat and Dog classes inherit from the Pet class.

An interface is shown similar to a class with an additional keyword <<interface>>. When a class implements an interface, it is shown similar to class inheritance except a dashed line is used instead of a solid line.

The AcademicStaff and the AdminStaff classes implement the SalariedStaff interface.

You can use italics or {abstract} (preferred) keyword to denote abstract classes/methods.

Example:

A UML sequence diagram captures the interactions between multiple objects for a given scenario.

Consider the code below.

class Machine {

    Unit producePrototype() {
        Unit prototype = new Unit();
        for (int i = 0; i < 5; i++) {
            prototype.stressTest();
        }
        return prototype;
    }
}

class Unit {

    public void stressTest() {

    }
}

Here is the sequence diagram to model the interactions for the method call producePrototype() on a Machine object.

Notation:

This sequence diagram shows some interactions between a human user and the Text UI of a CLI Minesweeper game.

The player runs the newgame action on the TextUi object which results in the TextUi showing the minefield to the player. Then, the player runs the clear x y command; in response, the TextUi object shows the updated minefield.

The :TextUi in the above example denotes an unnamed instance of the class TextUi. If there were two instances of TextUi in the diagram, they can be distinguished by naming them e.g. TextUi1:TextUi and TextUi2:TextUi.

Arrows representing method calls should be solid arrows while those representing method returns should be dashed arrows.

Note that unlike in object diagrams, the class/object name is not underlined in sequence diagrams.

[Common notation error] Activation bar too long: The activation bar of a method cannot start before the method call arrives and a method cannot remain active after the method had returned. In the two sequence diagrams below, the one on the left commits this error because the activation bar starts before the method Foo#xyz() is called and remains active after the method returns.

[Common notation error] Broken activation bar: The activation bar should remain unbroken from the point the method is called until the method returns. In the two sequence diagrams below, the one on the left commits this error because the activation bar for the method Foo#abc() is not contiguous, but appears as two pieces instead.

Notation:

• The arrow that represents the constructor arrives at the side of the box representing the instance.
• The activation bar represents the period the constructor is active.

The Logic object creates a Minefield object.

UML uses an X at the end of the lifeline of an object to show it's deletion.

Notation:

Note how the diagrams shows the deletion of the Minefield object

Notation:

The Player calls the mark x,y command or clear x y command repeatedly until the game is won or lost.

UML can show a method of an object calling another of its own methods.

Notation:

The markCellAt(...) method of a Logic object is calling its own updateState(...) method.

In this variation, the Book#write() method is calling the Chapter#getText() method which in turn does a call back by calling the getAuthor() method of the calling object.

UML uses alt frames to indicate alternative paths.

Notation:

Minefield calls the Cell#setMine if the cell is supposed to be a mined cell, and calls the Cell:setMineCount(...) method otherwise.

UML uses opt frames to indicate optional paths.

Notation:

Logic#markCellAt(...) calls Timer#start() only if it is the first move of the player.

UML uses par frames to indicate parallel paths.

Notation:

Logic is calling methods CloudServer#poll() and LocalServer#poll() in parallel.

If you show parallel paths in a sequence diagram, the corresponding Java implementation is likely to be multi-threaded because a normal Java program cannot do multiple things at the same time.

UML uses ref frame to allow a segment of the interaction to be omitted and shown as a separate sequence diagram. Reference frames help us to break complicated sequence diagrams into multiple parts or simply to omit details we are not interested in showing.

Notation:

The details of the get minefield appearance interactions have been omitted from the diagram.

Those details are shown in a separate sequence diagram given below.

To reduce clutter, activation bars and return arrows may be omitted if they do not result in ambiguities or loss of information. Informal operation descriptions such as those given in the example below can be used, if more precise details are not required for the task at hand.

A minimal sequence diagram

An object diagram shows an object structure at a given point of time.

An example object diagram:

Notation: