The following description of the Joys of the Programming Craft was taken (and emphasis added) from Chapter 1 of the famous book The Mythical Man-Month, by Frederick P. Brooks.

Why is programming fun? What delights may its practitioner expect as his reward?

First is the sheer joy of making things. As the child delights in his mud pie, so the adult enjoys building things, especially things of his own design. I think this delight must be an image of God's delight in making things, a delight shown in the distinctness and newness of each leaf and each snowflake.

Second is the pleasure of making things that are useful to other people. Deep within, you want others to use your work and to find it helpful. In this respect the programming system is not essentially different from the child's first clay pencil holder "for Daddy's office."

Third is the fascination of fashioning complex puzzle-like objects of interlocking moving parts and watching them work in subtle cycles, playing out the consequences of principles built in from the beginning. The programmed computer has all the fascination of the pinball machine or the jukebox mechanism, carried to the ultimate.

Fourth is the joy of always learning, which springs from the nonrepeating nature of the task. In one way or another the problem is ever new, and its solver learns something: sometimes practical, sometimes theoretical, and sometimes both.

Finally, there is the delight of working in such a tractable medium. The programmer, like the poet, works only slightly removed from pure thought-stuff. He builds his castles in the air, from air, creating by the exertion of the imagination. Few media of creation are so flexible, so easy to polish and rework, so readily capable of realizing grand conceptual structures....

Yet the program construct, unlike the poet's words, is real in the sense that it moves and works, producing visible outputs separate from the construct itself. It prints results, draws pictures, produces sounds, moves arms. The magic of myth and legend has come true in our time. One types the correct incantation on a keyboard, and a display screen comes to life, showing things that never were nor could be.

Programming then is fun because it gratifies creative longings built deep within us and delights sensibilities you have in common with all men.

Not all is delight, however, and knowing the inherent woes makes it easier to bear them when they appear.

First, one must perform perfectly. The computer resembles the magic of legend in this respect, too. If one character, one pause, of the incantation is not strictly in proper form, the magic doesn't work. Human beings are not accustomed to being perfect, and few areas of human activity demand it. Adjusting to the requirement for perfection is, I think, the most difficult part of learning to program.

Next, other people set one's objectives, provide one's resources, and furnish one's information. One rarely controls the circumstances of his work, or even its goal. In management terms, one's authority is not sufficient for his responsibility. It seems that in all fields, however, the jobs where things get done never have formal authority commensurate with responsibility. In practice, actual (as opposed to formal) authority is acquired from the very momentum of accomplishment.

The dependence upon others has a particular case that is especially painful for the system programmer. He depends upon other people's programs. These are often maldesigned, poorly implemented, incompletely delivered (no source code or test cases), and poorly documented. So he must spend hours studying and fixing things that in an ideal world would be complete, available, and usable.

The next woe is that designing grand concepts is fun; finding nitty little bugs is just work. With any creative activity come dreary hours of tedious, painstaking labor, and programming is no exception.

Next, one finds that debugging has a linear convergence, or worse, where one somehow expects a quadratic sort of approach to the end. So testing drags on and on, the last difficult bugs taking more time to find than the first.

The last woe, and sometimes the last straw, is that the product over which one has labored so long appears to be obsolete upon (or before) completion. Already colleagues and competitors are in hot pursuit of new and better ideas. Already the displacement of one's thought-child is not only conceived, but scheduled.

This always seems worse than it really is. The new and better product is generally not available when one completes his own; it is only talked about. It, too, will require months of development. The real tiger is never a match for the paper one, unless actual use is wanted. Then the virtues of reality have a satisfaction all their own.

Of course the technological base on which one builds is always advancing. As soon as one freezes a design, it becomes obsolete in terms of its concepts. But implementation of real products demands phasing and quantizing. The obsolescence of an implementation must be measured against other existing implementations, not against unrealized concepts. The challenge and the mission are to find real solutions to real problems on actual schedules with available resources.

This then is programming, both a tar pit in which many efforts have floundered and a creative activity with joys and woes all its own. For many, the joys far outweigh the woes....

Object-Oriented Programming (OOP) is a programming paradigm. A programming paradigm guides programmers to analyze programming problems, and structure programming solutions, in a specific way.

Programming languages have traditionally divided the world into two parts—data and operations on data. Data is static and immutable, except as the operations may change it. The procedures and functions that operate on data have no lasting state of their own; they’re useful only in their ability to affect data.

This division is, of course, grounded in the way computers work, so it’s not one that you can easily ignore or push aside. Like the equally pervasive distinctions between matter and energy and between nouns and verbs, it forms the background against which you work. At some point, all programmers—even object-oriented programmers—must lay out the data structures that their programs will use and define the functions that will act on the data.

With a procedural programming language like C, that’s about all there is to it. The language may offer various kinds of support for organizing data and functions, but it won’t divide the world any differently. Functions and data structures are the basic elements of design.

Object-oriented programming doesn’t so much dispute this view of the world as restructure it at a higher level. It groups operations and data into modular units called objects and lets you combine objects into structured networks to form a complete program. In an object-oriented programming language, objects and object interactions are the basic elements of design.

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

Some other examples of programming paradigms are:

Some programming languages support multiple paradigms.

An object in Object-Oriented Programming (OOP) has state and behavior, similar to objects in the real world.

Every object has both state (data) and behavior (operations on data). In that, they’re not much different from ordinary physical objects. It’s easy to see how a mechanical device, such as a pocket watch or a piano, embodies both state and behavior. But almost anything that’s designed to do a job does, too. Even simple things with no moving parts such as an ordinary bottle combine state (how full the bottle is, whether or not it’s open, how warm its contents are) with behavior (the ability to dispense its contents at various flow rates, to be opened or closed, to withstand high or low temperatures).

It’s this resemblance to real things that gives objects much of their power and appeal. They can not only model components of real systems, but equally as well fulfill assigned roles as components in software systems.

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

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 virtual simulation of the corresponding real world scenario – so that a similar result can be achieved programmatically.

OOP does not demand that the virtual world object network follow the real world exactly.

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

Every object has an interface and an implementation.

Every real world object has,

• an interface through which other objects can interact with it, and,
• 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 messages to each other. The message can result in the sender object receiving a response and/or the receiver object’s state being changed. Furthermore, the result can vary based on which object received the message, even if the message is identical (see rows 1 and 2 in the example below).

The concept of Objects in OOP is an abstraction mechanism because it allows us to abstract away the lower level details and work with bigger granularity entities i.e. ignore details of data formats and the method implementation details and work at the level of objects.

Encapsulation protects an implementation from unintended actions and from inadvertent access.
_{-- Object-Oriented Programming with Objective-C, Apple}

An object is an encapsulation of some data and related behavior in terms of two aspects:

1. The packaging aspect: An object packages data and related behavior together into one self-contained unit.

2. The information hiding aspect: The data in an object is hidden from the outside world and are only accessible using the object's interface.

Writing an OOP program is essentially writing instructions that the computer will use to,

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

A class contains instructions for creating a specific kind of objects. It turns out sometimes multiple objects keep the same type of data and have the same behavior because they are of the same kind. Instructions for creating a 'kind' (or ‘class’) of objects can be done once and those same instructions can be used to objects of that kind. We call such instructions a Class.

While all objects of a class have 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 messages to a specific object of that class. Such methods that are called using the class instead of a specific instance are called class-level methods.

Class-level attributes and methods are collectively called class-level members (also called static members sometimes because some programming languages use the keyword static to identify class-level members). They are to be accessed using the class name rather than an instance of the class.

An Enumeration is a fixed set of values that can be considered as a data type. An enumeration is often useful when using a regular data type such as int or String would allow invalid values to be assigned to a variable.

Objects in an OO solution need to be connected to each other to form a network so that they can interact with each other. Such connections between objects are called associations.

Associations in an object structure can change over time.

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

Implementing associations

You use instance level variables to implement associations.

When two classes are linked by an association, it does not necessarily mean the two objects taking part in an instance of the association knows about (i.e., has a reference to) each other. The concept of which object in the association knows about the other object is called navigability.

Navigability can be unidirectional or bidirectional. Suppose there is an association between the classes Box and Rope, and the Box object b and the Rope object r is taking part in one instance of that association.

• Unidirectional: If the navigability is from Box to Rope, b will have a reference to r but r will not have a reference to b. That is, one can navigate from b to r using the b's object reference of r (but not in the other direction).
  Similarly, if the navigability is in the other direction, r will have a reference to b but b will not have a reference to r.
• Bidirectional: b will have a reference to r and r will have a reference to b i.e., the two objects will be pointing to each other for the same single instance of the association.

Note that two unidirectional associations in opposite directions do not add up to a single bidirectional association.

class Person {
    Cat pet;
    //...
}

class Cat{
    Person owner;
    //...
}

    

    


    
    
    

      


    
    

class Person:

  def __init__(self):
    self.pet = None  # a Cat object


class Cat:

  def __init__(self):
    self.owner = None  # a Person object

    

    


    
    
    

      


    
    

class Person {
    Cat pet;
    //...
}

class Cat{
    Person breeder;
    //...
}

    

    


    
    
    

      


    
    

class Person:

  def __init__(self):
    self.pet = None  # a Cat object


class Cat:

  def __init__(self):
    self.breeder = None  # a Person object

    

    


    
    
    

      


    
    

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

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):
    self.minefield = None
    
  # ...


class Minefield:
  # ...

    

    


    
    
    

      


    
    

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

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

    

    


    
    
    

      


    
    

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 direct association in the same direction. Reason for the exclusion: If there is an association from class Foo to class Bar (i.e., navigable from Foo to Bar), that means Foo is obviously dependent on Bar and hence there is no point in mentioning dependency specifically. In other words, we are specifically focusing on non-obvious dependencies here. One cause of such dependencies is interactions between objects that do not have a long-term link between them.

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.

Composition implies,

1. when the whole is destroyed, parts are destroyed too i.e., the part cannot exist without being attached to a whole.
2. there cannot be cyclical links.

Whether a relationship is a composition can depend on the context.

A common use of composition is when parts of a big class are carved out as smaller classes for the ease of managing the internal design. In such cases, the classes extracted out still act as parts of the bigger class and the outside world has no business knowing about them.

Cascading deletion alone is not sufficient for composition. Suppose there is a design in which Person objects are attached to Task objects and the former get deleted whenever the latter is deleted. This fact alone does not mean there is a composition relationship between the two classes. For it to be composition, a Person must be an integral part of a Task in the context of that association, at the concept level (not simply at implementation level).

Identifying and keeping track of composition relationships in the design has benefits such as helping to maintain the data integrity of the system. For example, when you know that a certain relationship is a composition, you can take extra care in your implementation to ensure that when the whole object is deleted, all its parts are deleted too.

Implementing composition

Composition is implemented using a normal variable. If correctly implemented, the ‘part’ object will be deleted when the ‘whole’ object is deleted. Ideally, the ‘part’ object may not even be visible to clients of the ‘whole’ object.

class Email {
    private Subject subject;
  ...
}

    

    


    
    
    

      


    
    

class Email:

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

    

    


    
    
    

      


    
    

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

Implementing aggregation

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

class Team {
    Person leader;
    ...
    void setLeader(Person p) {
        leader = p;
    }
}

    

    


    
    
    

      


    
    

class Team:
  
  def __init__(self):
    self.__leader = None
    
  def set_leader(self, person):
    self.__leader = person

    

    


    
    
    

      


    
    

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;

    Transaction(Person seller, Person buyer, Date date, String receiptNumber) {
        //set fields
    }
}

    

    


    
    
    

      


    
    

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

• Other names for Base class: Parent class, Superclass
• Other names for Derived class: Child class, Subclass, 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 subtype of the base class (and the base class is a super-type of the derived class), resulting in an is a relationship.

Inheritance does not necessarily mean a subtype relationship exists. However, the two often go hand-in-hand. For simplicity, at this point let us assume inheritance implies a subtype relationship.

Inheritance relationships through a chain of classes can result in inheritance hierarchies (aka inheritance trees).

Two inheritance hierarchies/trees are given below. Note that the triangle points to the parent class. Observe how the Parrot is a Bird as well as it is an Animal.

Multiple Inheritance is when a class inherits directly from multiple classes. Multiple inheritance among classes is allowed in some languages (e.g., Python, C++) but not in other languages (e.g., Java, C#).

The Honey class inherits from the Food class and the Medicine class because honey can be consumed as a food as well as a medicine (in some oriental medicine practices). Similarly, a Car is a Vehicle, an Asset and a Liability.

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

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 . If a class , it means the class is able to support the behaviors specified by the said interface.

There are a number of situations in software engineering when it is important for disparate groups of programmers to agree to a "contract" that spells out how their software interacts. Each group should be able to write their code without any knowledge of how the other group's code is written. Generally speaking, interfaces are such contracts. _{--Oracle Docs on Java}

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

You can declare a class as abstract when a class is merely a representation of commonalities among its subclasses in which case it does not make sense to instantiate objects of that class.

A class that has an abstract method becomes an abstract class because the class definition is incomplete (due to the missing method body) and it is not possible to create objects using an incomplete class definition.

Every instance of a subclass is an instance of the superclass, but not vice-versa. As a result, inheritance allows substitutability: the ability to substitute a child class object where a parent class object is expected.

An AcademicStaff is an instance of a Staff, but a Staff is not necessarily an instance of an AcademicStaff. i.e. wherever an object of the superclass is expected, it can be substituted by an object of any of its subclasses.

The following code is valid because an AcademicStaff object is substitutable as a Staff object.

Staff staff = new AcademicStaff(); // OK

    

    


    
    
    

      


    
    

But the following code is not valid because staff is declared as a Staff type and therefore its value may or may not be of type AcademicStaff, which is the type expected by variable academicStaff.

Staff staff;
...
AcademicStaff academicStaff = staff; // Not OK

    

    


    
    
    

      


    
    

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

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 objects 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 is 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 brownfield project i.e., develop a product to replace/update an existing software product
• a greenfield project i.e., develop a totally new system from scratch

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

Requirements come from stakeholders.

Identifying requirements is often not easy. For example, stakeholders may not be aware of their precise needs, may not know how to communicate their requirements correctly, may not be willing to spend effort in identifying requirements, etc.

Requirements can be divided into two in the following way:

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

You 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 on the importance and urgency, while keeping in mind the constraints of schedule, budget, staff resources, quality goals, and other constraints.

A common approach is to group requirements into priority categories. Note that all such scales are subjective, and stakeholders define the meaning of each level in the scale for the project at hand.

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

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

• Unambiguous
• Testable (verifiable)
• Clear (concise, terse, simple, precise)
• Correct
• Understandable
• Feasible (realistic, possible)
• Independent
• 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 about project requirements.

Focus groups are a kind of informal interview within an interactive group setting. A group of people (e.g. potential users, beta testers) are asked about their understanding of a specific issue, process, product, advertisement, etc.

Prototyping can uncover requirements, in particular, those related to how users interact with the system. UI prototypes or mock ups are often used in brainstorming sessions, or in meetings with the users to get quick feedback from them.

Prototyping can be used for discovering as well as specifying requirements e.g. a UI prototype can serve as a specification of what to build.

Studying existing products can unearth shortcomings of existing solutions that can be addressed by a new product. Product manuals and other forms of documentation of an existing system can tell us how the existing solutions work.

A textual description (i.e. prose) can be used to describe requirements. Prose is especially useful when describing abstract ideas such as the vision of a product.

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

A common format for writing user stories is:

You can write user stories using a physical medium or a digital tool. For example, you can use index cards or sticky notes, and arrange them on walls or tables. Alternatively, you can use a software (e.g., GitHub Project Boards, Trello, Google Docs, ...) to manage user stories digitally.

User stories in use

With sticky notes

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

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With paper

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

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With software

^{[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 , , and .

[User stories] strongly shift the focus from writing about features to discussing them. In fact, these discussions are more important than whatever text is written. _{[Mike Cohn, MountainGoat Software 🔗]}

User stories differ from mainly in the level of detail. User stories should only provide enough details to make a reasonably low risk estimate of how long the user story will take to implement. When the time comes to implement the user story, the developers will meet with the customer face-to-face to work out a more detailed description of the requirements. [more...]

User stories can capture non-functional requirements too because even NFRs must benefit some stakeholder.

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

A use case describes an interaction between the user and the system for a specific functionality of the system.

System: Online Banking System (OBS)
Use case: UC23 - Transfer Money
Actor: User
MSS:
  1. User chooses to transfer money.
  2. OBS requests for details of the transfer.
  3. User enters the requested details.
  4. OBS requests for confirmation.
  5. User confirms.
  6. OBS transfers the money and displays the new account balance.
  Use case ends.

    

    


    
    
    

      


    
    

Extensions:
  3a. OBS detects an error in the entered data.
      3a1. OBS requests for the correct data.
      3a2. User enters new data.
      Steps 3a1-3a2 are repeated until the data entered are correct.
      Use case resumes from step 4.

  3b. User requests to effect the transfer in a future date.
      3b1. OBS requests for confirmation.
      3b2. User confirms future transfer.
      Use case ends.

  *a. At any time, User chooses to cancel the transfer.
      *a1. OBS requests to confirm the cancellation.
      *a2. User confirms the cancellation.
      Use case ends.

    

    


    
    
    

      


    
    

UML includes a diagram type called use case diagrams that can illustrate use cases of a system visually, providing a visual ‘table of contents’ of the use cases of a system.

In the example on the right, note how use cases are shown as ovals and user roles relevant to each use case are shown as stick figures connected to the corresponding ovals.

Use cases capture the functional requirements of a system.

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

The guiding principle of abstraction is that only details that are relevant to the current perspective or the task at hand need to be considered. As most programs are written to solve complex problems involving large amounts of intricate details, it is impossible to deal with all these details at the same time. That is where abstraction can help.

Data abstraction: abstracting away the lower level data items and thinking in terms of bigger entities

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

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

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

Coupling is a measure of the degree of dependence between components, classes, methods, etc. Low coupling indicates that a component is less dependent on other components. High coupling (aka tight coupling or strong coupling) is discouraged due to the following disadvantages:

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

In the example below, design A appears to have 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.

Cohesion is a measure of how strongly-related and focused the various responsibilities of a component are. A highly-cohesive component keeps related functionalities together while keeping out all other unrelated things.

Higher cohesion is better. Disadvantages of low cohesion (aka weak cohesion):

• Lowers the understandability of modules as it is difficult to express module functionalities at a higher level.
• Lowers maintainability because a module can be modified due to unrelated causes (reason: the module contains code unrelated to each other) or many modules may need to be modified to achieve a small change in behavior (reason: because the code related 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 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 documentation.

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 set by the designer of that software. Those rules that object structures need to follow can be illustrated as a class structure i.e. a structure that exists among the relevant classes.

UML Object Diagrams model object structures. UML Class Diagrams model class structures.

Contents related to UML diagrams in the panels given below belong to a different chapter (i.e., the chapter dedicated to UML); they have been embedded here for convenience.

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 relationships between classes: inheritance, compositions, aggregations, dependencies.

A class diagram can also show different types of class-like entities:

A class diagram can show association classes too.

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.

Sequence diagrams model the interactions between various entities in a system, in a specific scenario. Modelling such scenarios is useful, for example, to verify the design of the internal interactions is able to provide the expected outcomes.

Contents related to UML diagrams in the panels given below belong to a different chapter (i.e., the chapter dedicated to UML); they have been embedded here for convenience.

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 symbols that reasonably describe 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 bidirectional dependency with the Logic component is no longer captured.

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

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 use the client-server style.

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) written by Erich 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

Certain classes should have no more than just one instance (e.g. the main controller class of the system). These single instances are commonly known as singletons.

Problem

A normal class can be instantiated multiple times by invoking the constructor.

Solution

Make the constructor of the singleton class private, because a public constructor will allow others to instantiate the class at will. Provide a public class-level method to access the single instance.

Example:

The <<Singleton>> in the class above uses the UML stereotype notation, which is used to (optionally) indicate the purpose or the role played by a UML element. In this example, the class Logic is playing the role of a Singleton class. The general format is <<role/purpose>>.

Here is the typical implementation of how the Singleton pattern is applied to a class:

class Logic {
    private static Logic theOne = null;

    private Logic() {
        ...
    }

    public static Logic getInstance() {
        if (theOne == null) {
            theOne = new Logic();
        }
        return theOne;
    }
}

    

    


    
    
    

      


    
    

Notes:

• 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 codebase

Cons:

• The singleton object acts like a global variable that increases coupling across the codebase.
• 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 you want each test to be independent of the others.

Given that there are some significant cons, it is recommended that you apply the Singleton pattern when, in addition to requiring only one instance of a class, there is a risk of creating multiple objects by mistake, and creating such multiple objects has real negative consequences.

Context

Components need to access functionality deep inside other components.

The UI component of a Library system might want to access functionality of the Book class contained inside the Logic component.

Problem

Access to the component should be allowed without exposing its internal details. e.g. the UI component should access the functionality of the Logic component without knowing that it contains a Book class within it.

Solution

Include a class that sits between the component internals and users of the component such that all access to the component happens through the Facade class.

The following class diagram applies the Facade pattern to the Library System example. The LibraryLogic class is the Facade class.

Professional software engineers often write code using Integrated Development Environments (IDEs). IDEs support most development-related work within the same tool (hence, the term integrated).

An IDE generally consists of:

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

Examples of popular IDEs:

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

Some web-based IDEs have appeared in recent times too e.g., Amazon's Cloud9 IDE.

Some experienced developers, in particular those with a UNIX background, prefer lightweight yet powerful text editors with scripting capabilities (e.g. Emacs) over heavier IDEs.

Debugging is the process of discovering defects in the program. Here are some approaches to debugging:

• Bad -- By inserting temporary print statements: This is an ad-hoc approach in which print statements are inserted in the program to print information relevant to debugging, such as variable values. e.g. Exiting process() method, x is 5.347. This approach is not recommended due to these reasons:
  • Incurs extra effort when inserting and removing the print statements.
  • These extraneous program modifications increase the risk of introducing errors into the program.
  • These print statements, if not removed promptly after the debugging, may even appear unexpectedly in the production version.
• Bad -- By manually tracing through the code: Otherwise known as ‘eye-balling’, this approach doesn't have the cons of the previous approach, but it too is not recommended (other than as a 'quick try') due to these reasons:
  • It is a difficult, time consuming, and error-prone technique.
  • If you didn't spot the error while writing the code, you might not spot the error when reading the code either.
• Good -- Using a debugger: A debugger tool allows you to pause the execution, then step through the code 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 on software, poor quality code is something no one can afford to tolerate.

Programs should be written and polished until they acquire publication quality. _{--Niklaus Wirth}

Among various dimensions of code quality, such as run-time efficiency, security, and robustness, one of the most important is readability (aka understandability). This is because in any non-trivial software project, code needs to be read, understood, and modified by other developers later on. Even if you do not intend to pass the code to someone else, code quality is still important because you will become a 'stranger' to your own code someday.

Avoid long methods as they often contain more information than what the reader can process at a time. Consider if shortening is possible when a method goes beyond 30 . The bigger the haystack, the harder it is to find a needle.

If you need more than 3 levels of indentation, you're screwed anyway, and should fix your program. _{--Linux 1.3.53 Coding Style}

Avoid deep nesting -- the deeper the nesting, the harder it is for the reader to keep track of the logic.

In particular, avoid arrowhead style code.

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 (isAlreadySubsidized) {
        subsidy = SUBSIDIZED_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_subsidized:
        return SUBSIDIZED_SUBSIDY
    elif is_parttime:
        return FULLTIME_SUBSIDY * RATIO
    else:
        return FULLTIME_SUBSIDY

    

    


    
    
    

      


    
    

Avoid complicated expressions, especially those having many negations and nested parentheses. If you must evaluate complicated expressions, have it done in steps (i.e. calculate some intermediate values first and use them to calculate the final value).

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

    

    


    
    
    

      


    
    

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

boolean isUrgent = typeCode == URGENT;

return isValidCode && isUrgent;

    

    


    
    
    

      


    
    

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

    

    


    
    
    

      


    
    

is_within_size_limit = length < MAX_LENGTH
is_same_size = previous_size != length
is_valid_code = is_within_size_limit or is_same_size

is_urgent = type_code == URGENT

return is_valid_code and is_urgent

    

    


    
    
    

      


    
    

The competent programmer is fully aware of the strictly limited size of his own skull; therefore he approaches the programming task in full humility, and among other things he avoids clever tricks like the plague. _{-- Edsger Dijkstra}

Avoid magic numbers in your code. When the code has a number that does not explain the meaning of the number, it is called a "magic number" (as in "the number appears as if by magic"). Using a makes the code easier to understand because the name tells us more about the meaning of the number.

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

return "Error 1432"; // A magic string!

    

    


    
    
    

      


    
    

return "Error 1432" # A magic string!

    

    


    
    
    

      


    
    

Avoid any magic literals in general, not just magic numbers.

Make the code as explicit as possible, even if the language syntax allows them to be implicit. Here are some examples:

• [Java] Use explicit type conversion instead of implicit type conversion.
• [Java, Python] Use parentheses/braces to show groupings even when they can be skipped.
• [Java, Python] Use enumerations when a certain variable can take only a small number of finite values. For example, instead of declaring the variable 'state' as an integer and using values 0, 1, 2 to denote the states 'starting', 'enabled', and 'disabled' respectively, declare 'state' as type SystemState and define an enumeration SystemState that has values 'STARTING', 'ENABLED', and 'DISABLED'.

Lay out the code so that it adheres to the logical structure. The code should read like a story. Just like how you use section breaks, chapters and paragraphs to organize a story, use classes, methods, indentation and line spacing in your code to group related segments of the code. For example, you can use blank lines to separate groups of related statements.

Sometimes, the correctness of your code does not depend on the order in which you perform certain intermediary steps. Nevertheless, this order may affect the clarity of the story you are trying to tell. Choose the order that makes the story most readable.

statement A1
statement A2
statement A3
statement B1
statement C1
statement B2
statement C2

    

    


    
    
    

      


    
    

statement A1
statement A2
statement A3

statement B1
statement B2

statement C1
statement C2

    

    


    
    
    

      


    
    

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

• unused parameters in the method signature
• similar things that 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

Do not try to write ‘clever’ code. "Keep it simple, stupid” (KISS), as the old adage goes. For example, do not dismiss the brute-force yet simple solution in favor of a complicated one because of some ‘supposed benefits’ such as 'better reusability' unless you have a strong justification.

Debugging is twice as hard as writing the code in the first place. Therefore, if you write the code as cleverly as possible, you are, by definition, not smart enough to debug it. _{-- Brian W. Kernighan}

Programs must be written for people to read, and only incidentally for machines to execute. _{-- Abelson and Sussman}

Optimizing code prematurely has several drawbacks:

• You 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 readability.
• Hand-optimized code can be harder for the compiler to optimize (the simpler the code, the easier it is for the compiler to optimize). 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.

Make it work, make it right, make it fast is popular saying in the industry, which means in most cases, getting the code to perform correctly should take priority over optimizing it. If the code doesn't work correctly, it has no value no matter how fast/efficient it is.

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

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

Avoid having multiple levels of abstraction within a code fragment. Note: The book The Productive Programmer (by Neal Ford) calls this the Single Level of Abstraction Principle (SLAP) while the book Clean Code (by Robert C. Martin) calls this One Level of Abstraction per Function.

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

    

    


    
    
    

      


    
    

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

    

    


    
    
    

      


    
    

That said, it is sometimes possible to pack two levels of abstraction into the code without affecting readability that much, provided each step in the higher-level logic is clearly marked using comments and separated (e.g., using a blank line) from adjacent steps.

//high-level step A
low-level statement A1
low-level statement A2
low-level statement A3

//high-level step B
low-level statement B1
low-level statement B2

//high-level step C
low-level statement C1
low-level statement C2

    

    


    
    
    

      


    
    

The happy path should be clear and prominent in your code. Restructure the code to make the happy path (i.e. the execution path taken when everything goes well) less-nested as much as possible. It is the ‘unusual’ cases that should be nested. Someone reading the code should not get distracted by alternative paths taken when error conditions happen. One technique that could help in this regard is the use of guard clauses.

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();

    

    


    
    
    

      


    
    

for (condition1)
    if (condition2)
        statement A
        statement B
        statement C
        statement D
statement E

    

    


    
    
    

      


    
    

for (condition1)
    if (not condition2)
        continue
    statement A
    statement B
    statement C
    statement D
statement E

    

    


    
    
    

      


    
    

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

The aim of a coding standard is to make the entire codebase look like it was written by one person. A coding standard is usually specific to a programming language and specifies guidelines such as the locations of opening and closing braces, indentation styles and naming styles (e.g. whether to use Hungarian style, Pascal casing, Camel casing, etc.). It is important that the whole team/company uses the same coding standard and that the standard is generally not inconsistent with typical industry practices. If a company's coding standard is very different from what is typically used in the industry, new recruits will take longer to get used to the company's coding style.

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

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

Every system is built from a domain-specific language designed by the programmers to describe that system. Functions are the verbs of that language, and classes are the nouns.
_{-- Robert C. Martin, Clean Code: A Handbook of Agile Software Craftsmanship}

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

Distinguish clearly between single-valued and multi-valued variables.

Person student;
ArrayList<Person> students;

    

    


    
    
    

      


    
    

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

    

    


    
    
    

      


    
    

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

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 a 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.