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 that other objects can interact with
• 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 receiving 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 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 uses to,

1. create the virtual world of 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 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. You are recommended to enumeration types any time you need to represent a fixed set of constants.

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 classles 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()

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.

Implementing association classes

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.

class Transaction{
    
    //all fields are compulsory
    Person seller;
    Person buyer;
    Date date;
    String receiptNumber;
    
    Marriage (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.

• 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 use 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.

Evan a class that does not have any abstract methods can be declared as an abstract class.

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

Overridden methods are resolved using dynamic binding, and therefore resolves to the implementation in the actual type of the object.

Paradigms → Object Oriented Programming → Inheritance →

Overriding

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.

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).

Paradigms → Object Oriented Programming → Inheritance →

Overloading

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.

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

Which of these methods override another method? A is the parent class. B inherits A.

• a
• b
• c
• d
• e

d

Explanation: Method overriding requires a method in a child class to use the same method name and same parameter sequence used by one of its ancestors

void adjustSalary(int byPercent) {
    for (Staff s: staff) {
        s.adjustSalary(byPercent);
    }
}

In contrast, overloaded methods are resolved using static binding.

class Account {

    Account () {
        // Signature: ()
        ...
    }

    Account (String name, String number, double balance) {
        // Signature: (String, String, double)
        ...
    }
}

void calculateGrade (int[] averages) { ... }
void calculateGrade (String matric) { ... }

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".

Three concepts combine to achieve polymorphism: substitutability, operation overriding, and dynamic binding.

• Substitutability: Because of substitutability, you can write code that expects object of a parent class and yet use that code with objects of child classes. That is how polymorphism is able to treat objects of different types as one type.
• Overriding: To get polymorphic behavior from an operation, the operation in the superclass needs to be overridden in each of the subclasses. That is how overriding allows objects of different subclasses to display different behaviors in response to the same method call.
• Dynamic binding: Calls to overridden methods are bound to the implementation of the actual object's class dynamically during the runtime. That is how the polymorphic code can call the method of the parent class and yet execute the implementation of the child class.

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.

There are two kinds of requirements:

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.

Requirements can be prioritized based 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.

Some requirements can be discarded if they are considered ‘out of scope’.

Here are some characteristics of well-defined requirements ^{[📖 zielczynski]}:

• Unambiguous
• Testable (verifiable)
• Clear (concise, terse, simple, precise)
• Correct
• Understandable
• Feasible (realistic, possible)
• Independent
• Atomic
• Necessary
• Implementation-free (i.e. abstract)

Besides these criteria for individual requirements, the set of requirements as a whole should be

• Consistent
• Non-redundant
• Complete

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.

Studying existing products can unearth shortcomings of existing solutions that can be addressed by a new product. Product manuals and other forms of technical documentation of an existing system can be a good way to learn about 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 use case is an interaction between a system and its actors.

Actors in Use Cases

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.

💡 While modeling user-system interactions,

• Start with high level use cases and progressively work toward lower level use cases.
• Be mindful at which level of details you are working on and not to mix use cases of different levels.

Writing use case steps

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. OBS transfers the money and displays the new account balance.
  6. Use case ends.


• Extensions:
  1. 3a. OBS detects an error in the entered data.
     1. 3a1. OBS requests for the correct data.
     2. 3a2. User enters new data.
     3. Steps 3a1-3a2 are repeated until the data entered are correct.
     4. Use case resumes from step 4.
     
     
  2. 3b. User requests to effect the transfer in a future date.
     1. 3b1. OBS requests for confirmation.
     2. 3b2. User confirms future transfer.
     3. Use case ends.
     
     
  3. *a. At any time, User chooses to cancel the transfer.
     1. *a1. OBS requests to confirm the cancellation.
     2. *a2. User confirms the cancellation.
     3. Use case ends.
     
     
  4. *b. At any time, 120 seconds lapse without any input from the User.
     1. *b1. OBS cancels the transfer.
     2. *b2. OBS informs the User of the cancellation.
     3. Use case ends.

Note that the numbering style is not a universal rule but a widely used convention. Based on that convention,

• either of the extensions marked 3a. and 3b. can happen just after step 3 of the MSS.
• the extension marked as *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 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.

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. The guiding principle of abstraction stipulates that we capture only details that are relevant to the current perspective or the task at hand.

Ignoring lower level data items and thinking in terms of bigger entities is called data abstraction.

Control abstraction abstracts away details of the actual control flow to focus on tasks at a simplified level.

Abstraction can be applied repeatedly to obtain progressively higher levels of 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):

• Impedes 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.

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}

Class diagrams can also be used to model objects in the problem domain (i.e. to model how objects actually interact in the real world, before emulating them in the solution). Class diagrams are used to model the problem domain are called conceptual class diagrams or OO domain models (OODMs).

OO domain model of a snakes and ladders game is given below.

Description: 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.

The above OO domain model omits the ladder class for simplicity. It can be included in a similar fashion to the Snake class.

OODMs 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 an OO domain model because DatabaseConnection is something related to a software solution but not an entity in the problem domain.

OODMs 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.

OODM notation is similar to class diagram notation but typically omit 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. UML  activity diagrams (AD) can model workflows.  Flow charts is another type of diagrams that can model workflows. Activity diagrams are the UML equivalent of flow charts.

An example activity diagram _{[source:wikipeida]}:

The most basic activity diagram is simply a linear sequence of actions.

Some workflows have alternate paths where only one of the alternate paths is taken based on some condition.

In some workflows, multiple paths happen in parallel.

Use case diagrams model the mapping between features of a system and its user roles.

A simple use case diagram:

You can use models to analyze and design a 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,

• Is this class structure is able to produce the behavior we want?
• What API should each class have?
• Do we need more classes?

To answer those questions, you can analyze the how the objects of these classes will interact with each other to produce the behavior you want.

As mentioned in [ Design → Modeling → Modeling a Solutions → Introduction], this is the Minesweeper design you have come up with so far. Our objective is to analyze, evaluate, and refine that design.

Design → Modeling → Modeling a Solution →

Introduction

You can use models to analyze and design a 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,

• Is this class structure is able to produce the behavior we want?
• What API should each class have?
• Do we need more classes?

To answer those questions, you can analyze the how the objects of these classes will interact with each other to produce the behavior you want.

Let us start by modelling 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 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 we conceptualized in our modelling 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 Text UI for the whole 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 interface
• TextUi: Textual user interface
• ATD: An automated test driver used for testing the game logic
• Logic: computation and logic of the game
• Store: 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 symbol that reasonably describes the architecture may be used.

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 bi-directional dependency with the Logic component is no longer captured.

Software architectures follow various high-level styles (aka architectural patterns), just like building architectures follow various architecture styles.

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.

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 uses 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 tellers 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 events 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.

Most applications use a mix of these architectural styles.

In software development, there are certain problems that recur in a certain context.

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) book written by Eric Gamma, Richard Helm, Ralph Johnson,and John Vlissides

The common format to describe a pattern consists of the following components:

• Context: The situation or scenario where the design problem is encountered.
• Problem: The main difficulty to be resolved.
• Solution: The core of the solution. It is important to note that the solution presented only includes the most general details, which may need further refinement for a specific context.
• Anti-patterns (optional): Commonly used solutions, which are usually incorrect and/or inferior to the Design Pattern.
• Consequences (optional): Identifying the pros and cons of applying the pattern.
• Other useful information (optional): Code examples, known uses, other related patterns, etc.

Context

A 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:

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:

• The constructor is private, which prevents instantiation from outside the class.
• The single instance of the singleton class is maintained by a private class-level variable.
• Access to this object is provided by a 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, an object is created like this:

Logic m = new Logic();

But now, the Logic object needs to be accessed like this:

Logic m = Logic.getInstance();

Pros:

• easy to apply
• effective in achieving its goal with minimal extra work
• provides an easy way to access the singleton object from anywhere in the code base

Cons:

• The singleton object acts like a global variable that increases coupling across the code base.
• In testing, it is difficult to replace Singleton objects with stubs (static methods cannot be overridden)
• In testing, singleton objects carry data from one test to another even when we want each test to be independent of the others.

Given 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 contained a Book class within it.

Solution

Include a Façade 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 Façade 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

To reduce coupling resulting from the interlinked nature of the features described above.

Solution

To decouple data, presentation, and control logic of an application by separating them into three different components: Model, View and Controller.

• View: Displays data, interacts with the user, and pulls data from the model if necessary.
• Controller: Detects UI events such as mouse clicks, button pushes and takes follow up action. Updates/changes the model/view when necessary.
• Model: Stores and maintains data. Updates views if necessary.

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 data of one 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.

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.

Here is a scenario from the 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 and
• StudentStatsUi: 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.

Context

An object (possibly, more than one) is interested to get notified when a change happens to another object. That is, some objects want to ‘observe’ another object.

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.

StudentList studentList = new StudentList();
StudentListUi listUi = new StudentListUi();
StudentStatusUi statusUi = new StudentStatsUi();

studentList.addUi(listUi);
studentList.addUi(statusUi);

//StudentList class
public void addUi(Observer o) {
    observerList.add(o);
}

//StudentList class
public void notifyUIs() {
    for(Observer o: observerList) //for each observer in the list
        o.update();
}

//StudentListUI class
public void update() {
    //refresh UI by pulling data from StudentList
}

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.
• The << Observable >> maintains a list of << Observer >> objects. addObserver(Observer) operation adds a new << Observer >> to the list of << Observer >>s.
• Whenever there is a change in the << 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 has inbuilt support for the Observer pattern.

In a smaller system, design of the entire system can be shown in one place.

This class diagram of se-edu/addressbook-level3 depicts the design of the entire software.

Design of bigger systems needs to be done/shown at multiple levels.

This architecture diagram of se-edu/addressbook-level4 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.

• Top-down: Design the high-level design first and flesh out the lower levels later. This is especially useful when designing big and novel systems where the high-level design needs to be stable before lower levels can be designed.
• Bottom-up: Design lower level components first and put them together to create the higher-level systems later. This is not usually scalable for bigger systems. One instance where this approach might work is when designing a variations of an existing system or re-purposing existing components to build a new system.
• Mix: Design the top levels using the top-down approach but switch to a bottom-up approach when designing the bottom levels.

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 all development-related work within the same tool.

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.
  • Unnecessary program modifications increases the risk of introducing errors into the program.
  • These print statements, if not promptly removed, 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.

Example:

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!

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.

Avoid things that would make the reader go ‘huh?’, such as,

• unused parameters in the method signature
• similar things look different
• different things that look similar
• multiple statements in the same line
• data flow anomalies such as, pre-assigning values to variables and modifying it without any use of the pre-assigned value

As the old adage goes, "keep it simple, stupid” (KISS). Do not try to write ‘clever’ code. 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:

• We may not know which parts are the real performance bottlenecks. This is especially the case when the code undergoes transformations (e.g. compiling, minifying, transpiling, etc.) before it becomes an executable. Ideally, you should use a profiler tool to identify the actual bottlenecks of the code first, and optimize only those parts.
• Optimizing can complicate the code, affecting correctness and understandability
• Hand-optimized code can be harder for the compiler to optimize (the simpler the code, the easier for the compiler to optimize it). In many cases a compiler can do a better job of optimizing the runtime code if you don't get in the way by trying to hand-optimize the source code.

A popular saying in the industry is make it work, make it right, make it fast 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 on matter how fast/efficient it it.

Premature optimization is the root of all evil in programming. _{--Donald Knuth}

Note that there are cases where optimizing takes priority over other things e.g. when writing code for resource-constrained environments. This guideline simply a caution that you should optimize only when it is really needed.

Avoid varying the level of abstraction within a code fragment. Note: The Productive Programmer (by Neal Ford) calls this the SLAP principle i.e. Single Level of Abstraction Per method.

readData();
salary = basic*rise+1000;
tax = (taxable?salary*0.07:0);
displayResult();

readData();
processData();
displayResult();

The happy path (i.e. the execution path taken when everything goes well) should be clear and prominent in your code. Restructure the code to make the happy path unindented as much as possible. It is the ‘unusual’ cases that should be indented. 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.

if (!isUnusualCase) {  //detecting an unusual condition
    if (!isErrorCase) {
        start();    //main path
        process();
        cleanup();
        exit();
    } else {
        handleError();
    }
} else {
    handleUnusualCase(); //handling that unusual condition
}

if (isUnusualCase) { //Guard Clause
    handleUnusualCase();
    return;
}

if (isErrorCase) { //Guard Clause
    handleError();
    return;
}

start();
process();
cleanup();
exit();

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}

Use nouns for classes/variables and verbs for methods/functions.

Distinguish clearly between single-valued and multivalued variables.

Person student;
ArrayList<Person> students;

student = Person('Jim')
students = [Person('Jim'), Person('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

A name is not just for differentiation; it should explain the named entity to the reader accurately and at a sufficient level of detail.

If the name has multiple words, they should be in a sensible order.

Imagine going to the doctor's and saying "My eye1 is swollen"! Don’t use numbers or case to distinguish names.

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.

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.

It is safer to use language constructs in the way they are meant to be used, even if the language allows shortcuts. Some such coding practices are common sources of bugs. Know them and avoid them.

Always include a default branch in case statements.

Furthermore, use it 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, throw an exception). 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.

if (red) print "red";
else print "blue";

if (red) print "red";
else if (blue) print "blue";
else error("incorrect input");

• Use one variable for one purpose. Do not reuse a variable for a different purpose other than its intended one, just because the data type is the same.
• Do not reuse formal parameters as local variables inside the method.

double computeRectangleArea(double length, double width) {
    length = length * width;
    return length;
}

double computeRectangleArea(double length, double width) {
    double area;
    area = length * width;
    return area;
}

Never write an empty catch statement. At least give a comment to explain why the catch block is left empty.

We all feel reluctant to delete code we have painstakingly written, even if we have no use for that code any more ("I spent a lot of time writing that code; what if we need it again?"). Consider all code as baggage you have to carry; get rid of unused code the moment it becomes redundant. 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}

Resources:

• Refactoring: Reduce Scope of Variable

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'. 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'.

Bad

// increment x
x++;

//trim the input
trimInput();

Do not write comments as if they are private notes to self. 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"""
    ...

Comments should explain what and why aspect of the code, rather than the how aspect.

👍 What : The specification of what the code supposed to do. The reader can compare such comments to the implementation to verify if the implementation is correct

/** Removes all spaces from the {@code input} */
void compact(String input){
    input.trim();
}

👍 Why : The rationale for the current implementation.

// 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.

// return true if both left end and right end are correct or the size has not incremented
return (left && right) || (input.size() == size);

boolean isSameSize = (input.size() == size) ;
return (isLeftEndCorrect && isRightEndCorrect) || isSameSize;

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 Number with Symbolic Constant
6. Replace Nested Conditional with Guard Clauses
7. Replace Parameter with Explicit Methods
8. Reverse Conditional
9. Split Loop
10. Split Temporary Variable

Developer-to-developer documentation can be in one of two forms:

1. Documentation for developer-as-user: Software components are written by developers and reused by other developers, which means there is a need to document how such components are to be used. Such documentation can take several forms:
   • API documentation: APIs expose functionality in small-sized, independent and easy-to-use chunks, each of which can be documented systematically.
   • Tutorial-style instructional documentation: In addition to explaining functions/methods independently, some higher-level explanations of how to use an API can be useful.

2. Documentation for developer-as-maintainer: There is a need to document how a system or a component is designed, implemented and tested so that other developers can maintain and evolve the code. Writing documentation of this type is harder because of the need to explain complex internal details. However, given that readers of this type of documentation usually have access to the source code itself, only some information need to be included in the documentation, as code (and code comments) can also serve as a complementary source of information.

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.

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 too.

Here are some tips on writing effective documentation.

• Use plenty of diagrams: It is not enough to explain something in words; complement it with visual illustrations (e.g. a UML diagram).
• Use plenty of examples: When explaining algorithms, show a running example to illustrate each step of the algorithm, in parallel to worded explanations.
• Use simple and direct explanations: Convoluted explanations and fancy words will annoy readers. Avoid long sentences.
• Get rid of statements that do not add value: For example, 'We made sure our system works perfectly' (who didn't?), 'Component X has its own responsibilities' (of course it has!).
• It is not a good idea to have separate sections for each type of artifact, such as 'use cases', 'sequence diagrams', 'activity diagrams', etc. Such a structure, coupled with the indiscriminate inclusion of diagrams without justifying their need, indicates a failure to understand the purpose of documentation. Include diagrams when they are needed to explain something. If you want to provide additional diagrams for completeness' sake, include them in the appendix as a reference.

Aim for 'just enough' developer documentation.

• Writing and maintaining developer documents is an overhead. You should try to minimize that overhead.
• If the readers are developers who will eventually read the code, the documentation should complement the code and should provide only just enough guidance to get started.

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 or text. When describing several similar algorithms/designs/APIs, etc., do not simply duplicate large chunks of text. Instead, describe the similarity 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 doc comments in source. In addition, modern IDEs use JavaDoc comments to generate explanatory tool tips.

/**
 * 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;
        }
 }

• A short tutorial on writing JavaDoc comments -- from tutorialspoint.com
• A more detailed description --from Oracle

AsciiDoc is similar to Markdown but has more powerful (but also more complex) syntax.

• AsciiDoc Writers Guide --from Asciidoctor.org

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.

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 intensity.

import java.util.logging.*;

private static Logger logger = Logger.getLogger("Foo");

// 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 we 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.

class MainApp{
    Config config;
    
    /** Returns the config object */
    Config getConfig(){
        return config;
    }
}

    /** 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. We 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:

• How critical is the system?
• Will the code be used by programmers other than the author?
• The level of programming language support for defensive programming
• The overhead of being defensive

Combining parts of a software product to form a whole is called integration. It is also one of the most troublesome tasks and it rarely goes smoothly.

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.

Early and frequent: integrate early and evolve each part in parallel, in small steps, re-integrating frequently.

Big-bang integration: integrate all components at the same time.

Incremental integration: integrate few components at a time. This approach is better than the 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 source code can be a complex multi-step process.  For example, it can include steps such as to 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 to compile, link and package 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 to this build process to some extent.

However, most big projects use specialized build tools to automate complex build processes.

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.

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.

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:

• 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.

• Pull Request reviews

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

• 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 for 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 is caused by a defect (or a bug).

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 a software. The higher the testability, the easier it is to achieve a better quality software.

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.

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

A proper unit test requires the unit to be tested in isolation so that bugs in the dependencies cannot influence the test  i.e. bugs outside of the unit should not affect the unit tests.

Stubs can isolate the SUT from its dependencies.

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
    }
}

Logic logic = new Logic(new DatabaseStorage());
String name = logic.getName(23);