More concretely, a method m of an object O should invoke only the methods of the following kinds of objects:

• The object O itself
• Objects passed as parameters of m
• Objects created/instantiated in m
• Objects from the direct association of O

void foo(Bar b) {
    Goo g = b.getGoo();
    g.doSomething();
}

LoD aims to reduce coupling by limiting the interaction to a closely related group of classes.

The five OOP principles given below are known as SOLID Principles (an acronym made up of the first letter of each principle):

Supplmentary → Principles →

Open-Closed Principle

While it is possible to isolate the functionalities of a software system into modules, there is no way to remove interaction between modules. When modules interact with each other, coupling naturally increases. Consequently, it is harder to localize any changes to the software system. The Open-Close Principle aims to alleviate this problem.

Open-Closed Principle (OCP): A module should be open for extension but closed for modification. That is, modules should be written so that they can be extended, without requiring them to be modified. _{-- proposed by Bertrand Meyer}

In object-oriented programming, OCP can be achieved in various ways. This often requires separating the specification (i.e. interface) of a module from its implementation.

In the design given below, the behavior of the CommandQueue class can be altered by adding more concrete Command subclasses. For example, by including a Delete class alongside List, Sort, and Reset, the CommandQueue can now perform delete commands without modifying its code at all. That is, its behavior was extended without having to modify its code. Hence, it was open to extensions, but closed to modification.

The behavior of a Java generic class can be altered by passing it a different class as a parameter. In the code below, the ArrayList class behaves as a container of Students in one instance and as a container of Admin objects in the other instance, without having to change its code. That is, the behavior of the ArrayList class is extended without modifying its code.

ArrayList students = new ArrayList< Student >();
ArrayList admins = new ArrayList< Admin >();  	

Which of these is closest to the meaning of the open-closed principle?

• a. We should be able to change a software module’s behavior without modifying its code.
• b. A software module should remain open to modification as long as possible.
• c. A software module should be open to modification and closed to extension.
• d. Open source software rocks. Closed source software sucks.

(a)

Explanation: Please refer the handout for the definition of OCP.

Supplmentary → Principles →

Liskov Substitution Principle

Liskov Substitution Principle (LSP): Derived classes must be substitutable for their base classes. _{-- proposed by Barbara Liskov}

LSP sounds same as substitutability but it goes beyond substitutability; LSP implies that a subclass should not be more restrictive than the behavior specified by the superclass. As we know, Java has language support for substitutability. However, if LSP is not followed, substituting a subclass object for a superclass object can break the functionality of the code.

Paradigms → Object Oriented Programming → Inheritance →

Substitutability

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

Suppose the Payroll class depends on the adjustMySalary(int percent) method of the Staff class. Furthermore, the Staff class states that the adjustMySalary method will work for all positive percent values. Both Admin and Academic classes override the adjustMySalary method.

Now consider the following:

• Admin#adjustMySalary method works for both negative and positive percent values.
• Academic#adjustMySalary method works for percent values 1..100 only.

In the above scenario,

• Admin class follows LSP because it fulfills Payroll’s expectation of Staff objects (i.e. it works for all positive values). Substituting Admin objects for Staff objects will not break the Payroll class functionality.
• Academic class violates LSP because it will not work for percent values over 100 as expected by the Payroll class. Substituting Academic objects for Staff objects can potentially break the Payroll class functionality.

The Rectangle#resize() can take any integers for height and width. This contract is violated by the subclass Square#resize() because it does not accept a height that is different from the width.

class Rectangle {
    ...
    /** sets the size to given height and width*/
    void resize(int height, int width){
        ...
    }
}


class Square extends Rectangle {
    
    @Override
    void resize(int height, int width){
        if (height != width) {
            //error
       }
    }
}

Now consider the following method that is written to work with the Rectangle class.

void makeSameSize(Rectangle original, Rectangle toResize){
    toResize.resize(original.getHeight(), original.getWidth());
}

This code will fail if it is called as maekSameSize(new Rectangle(12,8), new Square(4, 4)) That is, Square class is not substitutable for the Rectangle class.

If a subclass imposes more restrictive conditions than its parent class, it violates Liskov Substitution Principle.

• True
• False

True.

Explanation: If the subclass is more restrictive than the parent class, code that worked with the parent class may not work with the child class. Hence, the substitutability does not exist and LSP has been violated.

Supplmentary → Principles →

Interface Segregation Principle

Interface Segregation Principle (ISP): No client should be forced to depend on methods it does not use.

The Payroll class should not depend on the AdminStaff class because it does not use the arrangeMeeting() method. Instead, it should depend on the SalariedStaff interface.

public class Payroll {
    //...    
    private void adjustSalaries(AdminStaff adminStaff){ //violates ISP
        //...
    }

}

public class Payroll {
    //...    
    private void adjustSalaries(SalariedStaff staff){ //does not violate ISP
        //...
    }
}

Supplmentary → Principles →

Dependency Inversion Principle

The Dependency Inversion Principle states that,

1. High-level modules should not depend on low-level modules. Both should depend on abstractions.
2. Abstractions should not depend on details. Details should depend on abstractions.

Example:

In design (a), the higher level class Payroll depends on the lower level class Employee, a violation of DIP. In design (b), both Payroll and Employee depends on the Payee interface (note that inheritance is a dependency).

Design (b) is more flexible (and less coupled) because now the Payroll class need not change when the Employee class changes.

Which of these statements is true about the Dependency Inversion Principle.

• a. It can complicate the design/implementation by introducing extra abstractions, but it has some benefits.
• b. It is often used during testing, to replace dependencies with mocks.
• c. It reduces dependencies in a design.
• d. It advocates making higher level classes to depend on lower level classes.

• a. It can complicate the design/implementation by introducing extra abstractions, but it has some benefits.
• b. It is often used during testing, to replace dependencies with mocks.
• c. It reduces dependencies in a design.
• d. It advocates making higher level classes to depend on lower level classes.

Explanation: Replacing dependencies with mocks is Dependency Injection, not DIP. DIP does not reduce dependencies, rather, it changes the direction of dependencies. Yes, it can introduce extra abstractions but often the benefit can outweigh the extra complications.

The principle says that some capability we presume our software needs in the future should not be built now because the chances are "you aren't gonna need it". The rationale is that we do not have perfect information about the future and therefore some of the extra work we do to fulfill a potential future need might go to waste when some of our predictions fail to materialize.

This principle guards against duplication of information.

Explanation: The additional communication overhead will outweigh the benefit of adding extra manpower, especially if done near to a deadline.

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.

The rake notation is used to indicate that a part of the activity is given as a separate diagram.

Here is the AD for a game of ‘Snakes and Ladders’.

The rake symbol (in the Move piece action above) is used to show that the action is described in another subsidiary activity diagram elsewhere. That diagram is given below.

It is possible to partition an activity diagram to show who is doing which action. Such partitioned activity diagrams are sometime called swimlane diagrams.

A simple example of a swimlane diagram:

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.

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.

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.

Except for trivial SUTs, exhaustive testing is not practical because such testing often requires a massive/infinite number of test cases.

Program testing can be used to show the presence of bugs, but never to show their absence!
_{--Edsger Dijkstra}

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

1. Scripted testing: First write a set of test cases based on the expected behavior of the SUT, and then perform testing based on that set of test cases.

2. Exploratory testing: Devise test cases on-the-fly, creating new test cases based on the results of the past test cases.

Exploratory testing is ‘the simultaneous learning, test design, and test execution’ [source: bach-et-explained] whereby the nature of the follow-up test case is decided based on the behavior of the previous test cases. In other words, running the system and trying out various operations. It is called exploratory testing because testing is driven by observations during testing. Exploratory testing usually starts with areas identified as error-prone, based on the tester’s past experience with similar systems. One tends to conduct more tests for those operations where more faults are found.

Which approach is better – scripted or exploratory? A mix is better.

The success of exploratory testing depends on the tester’s prior experience and intuition. Exploratory testing should be done by experienced testers, using a clear strategy/plan/framework. Ad-hoc exploratory testing by unskilled or inexperienced testers without a clear strategy is not recommended for real-world non-trivial systems. While exploratory testing may allow us to detect some problems in a relatively short time, it is not prudent to use exploratory testing as the sole means of testing a critical system.

Scripted testing is more systematic, and hence, likely to discover more bugs given sufficient time, while exploratory testing would aid in quick error discovery, especially if the tester has a lot of experience in testing similar systems.

In some contexts, you will achieve your testing mission better through a more scripted approach; in other contexts, your mission will benefit more from the ability to create and improve tests as you execute them. I find that most situations benefit from a mix of scripted and exploratory approaches. -- [source: bach-et-explained]

A positive test case is when the test is designed to produce an expected/valid behavior. A negative test case is designed to produce a behavior that indicates an invalid/unexpected situation, such as an error message.

Test case design can be of three types, based on how much of SUT internal details are considered when designing test cases:

• Black-box (aka specification-based or responsibility-based) approach: test cases are designed exclusively based on the SUT’s specified external behavior.

• White-box (aka glass-box or structured or implementation-based) approach: test cases are designed based on what is known about the SUT’s implementation, i.e. the code.

• Gray-box approach: test case design uses some important information about the implementation. For example, if the implementation of a sort operation uses different algorithms to sort lists shorter than 1000 items and lists longer than 1000 items, more meaningful test cases can then be added to verify the correctness of both algorithms.

Use cases can be used for system testing and acceptance testing. For example, the main success scenario can be one test case while each variation (due to extensions) can form another test case. However, note that use cases do not specify the exact data entered into the system. Instead, it might say something like user enters his personal data into the system. Therefore, the tester has to choose data by considering equivalence partitions and boundary values. The combinations of these could result in one use case producing many test cases.

To increase E&E of testing, high-priority use cases are given more attention. For example, a scripted approach can be used to test high priority test cases, while an exploratory approach is used to test other areas of concern that could emerge during testing.

Consider the testing of the following operation.

It is inefficient and impractical to test this method for all integer values [-MIN_INT to MAX_INT]. Fortunately, there is no need to test all possible input values. For example, if the input value 233 failed to produce the correct result, the input 234 is likely to fail too; there is no need to test both.

In general, most SUTs do not treat each input in a unique way. Instead, they process all possible inputs in a small number of distinct ways. That means a range of inputs is treated the same way inside the SUT. Equivalence partitioning (EP) is a test case design technique that uses the above observation to improve the E&E of testing.

By dividing possible inputs into equivalence partitions we can,

• avoid testing too many inputs from one partition. Testing too many inputs from the same partition is unlikely to find new bugs. This increases the efficiency of testing by reducing redundant test cases.
• ensure all partitions are tested. Missing partitions can result in bugs going unnoticed. This increases the effectiveness of testing by increasing the chance of finding bugs.

Equivalence partitions (EPs) are usually derived from the specifications of the SUT.

When the SUT has multiple inputs, you should identify EPs for each input.

An EP may not have adjacent values.

Some inputs have only a small number of possible values and a potentially unique behavior for each value. In those cases we have to consider each value as a partition by itself.

Note that the EP technique is merely a heuristic and not an exact science, especially when applied manually (as opposed to using an automated program analysis tool to derive EPs). The partitions derived depend on how one ‘speculates’ the SUT to behave internally. Applying EP under a glass-box or gray-box approach can yield more precise partitions.

When deciding EPs of OOP methods, we need to identify EPs of all data participants that can potentially influence the behaviour of the method, such as,

• the target object of the method call
• input parameters of the method call
• other data/objects accessed by the method such as global variables. This category may not be applicable if using the black box approach (because the test case designer using the black box approach will not know how the method is implemented)

Boundary Value Analysis (BVA) is test case design heuristic that is based on the observation that bugs often result from incorrect handling of boundaries of equivalence partitions. This is not surprising, as the end points of the boundary are often used in branching instructions etc. where the programmer can make mistakes.

BVA suggests that when picking test inputs from an equivalence partition, values near boundaries (i.e. boundary values) are more likely to find bugs.

Boundary values are sometimes called corner cases.

Typically, we choose three values around the boundary to test: one value from the boundary, one value just below the boundary, and one value just above the boundary. The number of values to pick depends on other factors, such as the cost of each test case.