Week 8 [Fri, Mar 5th] - Topics

Contents of the panels given below belong to a different chapter; they have been embedded here for convenience and are collapsed by default to avoid content duplication in the printed version.

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:

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.

Compared to the notation for class diagrams, object diagrams differ in the following ways:

• Show objects instead of classes:
  • Instance name may be shown
  • There is a : before the class name
  • Instance and class names are underlined
• Methods are omitted
• Multiplicities are omitted

Furthermore, multiple object diagrams can correspond to a single class diagram.

Both object diagrams are derived from the same class diagram shown earlier. In other words, each of these object diagrams shows ‘an instance of’ the same class diagram.

UML notes can augment UML diagrams with additional information. These notes can be shown connected to a particular element in the diagram or can be shown without a connection. The diagram below shows examples of both.

Example:

An association can be shown as an attribute instead of a line.

Association multiplicities and the default value can be shown as part of the attribute using the following notation. Both are optional.

name: type [multiplicity] = default value

The diagram below depicts a multi-player Square Game being played on a board comprising of 100 squares. Each of the squares may be occupied with any number of pieces, each belonging to a certain player.

A Piece may or may not be on a Square. Note how that association can be replaced by an isOn attribute of the Piece class. The isOn attribute can either be null or hold a reference to a Square object, matching the 0..1 multiplicity of the association it replaces. The default value is null.

The association that a Board has 100 Squares can be shown in either of these two ways:

Show each association as either an attribute or a line but not both. A line is preferred as it is easier to spot.

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:

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
    }
}

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

Notation:

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

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

UML uses par frames to indicate parallel paths.

Notation:

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

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

Integration testing : testing whether different parts of the software work together (i.e. integrates) as expected. Integration tests aim to discover bugs in the 'glue code' related to how components interact with each other. These bugs are often the result of misunderstanding what the parts are supposed to do vs what the parts are actually doing.

Integration testing is not simply a case of repeating the unit test cases using the actual dependencies (instead of the stubs used in unit testing). Instead, integration tests are additional test cases that focus on the interactions between the parts.

In practice, developers often use a hybrid of unit+integration tests to minimize the need for stubs.

System testing is typically done by a testing team (also called a QA team).

System test cases are based on the specified external behavior of the system. Sometimes, system tests go beyond the bounds defined in the specification. This is useful when testing that the system fails 'gracefully' when pushed beyond its limits.

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

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

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

If a software product has a GUI (Graphical User Interface) component, all product-level testing (i.e. the types of testing mentioned above) need to be done using the GUI. However, testing the GUI is much harder than testing the CLI (Command Line Interface) or API, for the following reasons:

• Most GUIs can support a large number of different operations, many of which can be performed in any arbitrary order.
• GUI operations are more difficult to automate than API testing. Reliably automating GUI operations and automatically verifying whether the GUI behaves as expected is harder than calling an operation and comparing its return value with an expected value. Therefore, automated regression testing of GUIs is rather difficult.
• The appearance of a GUI (and sometimes even behavior) can be different across platforms and even environments. For example, a GUI can behave differently based on whether it is minimized or maximized, in focus or out of focus, and in a high resolution display or a low resolution display.

Moving as much logic as possible out of the GUI can make GUI testing easier. That way, you can bypass the GUI to test the rest of the system using automated API testing. While this still requires the GUI to be tested, the number of such test cases can be reduced as most of the system will have been tested using automated API testing.

There are testing tools that can automate GUI testing.

Acceptance tests give an assurance to the customer that the system does what it is intended to do. Acceptance test cases are often defined at the beginning of the project, usually based on the use case specification. Successful completion of UAT is often a prerequisite to the project sign-off.

Acceptance testing comes after system testing. Similar to system testing, acceptance testing involves testing the whole system.

Some differences between system testing and acceptance testing:

Note: negative test cases: cases where the SUT is not expected to work normally e.g. incorrect inputs; positive test cases: cases where the SUT is expected to work normally

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

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

Alpha testing is performed by the users, under controlled conditions set by the software development team.

Beta testing is performed by a selected subset of target users of the system in their natural work setting.

An open beta release is the release of not-yet-production-quality-but-almost-there software to the general population. For example, Google’s Gmail was in 'beta' for many years before the label was finally removed.

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]

Dependency injection is the process of 'injecting' objects to replace current dependencies with a different object. This is often used to inject stubs to isolate the Software Under TestSUT from its objects it depends ondependencies so that it can be tested in isolation.

A Foo object normally depends on a Bar object, but you can inject a BarStub object so that the Foo object no longer depends on a Bar object. Now you can test the Foo object in isolation from the Bar object.

Testability is an indication of how easy it is to test an SUT. As testability depends a lot on the design and implementation, you should try to increase the testability when you design and implement software. The higher the testability, the easier it is to achieve better quality software.

Test coverage is a metric used to measure the extent to which testing exercises the code i.e., how much of the code is 'covered' by the tests.

Here are some examples of different coverage criteria:

• Function/method coverage : based on functions executed e.g., testing executed 90 out of 100 functions.
• Statement coverage : based on the number of lines of code executed e.g., testing executed 23k out of 25k LOC.
• Decision/branch coverage : based on the decision points exercised e.g., an if statement evaluated to both true and false with separate test cases during testing is considered 'covered'.
• Condition coverage : based on the boolean sub-expressions, each evaluated to both true and false with different test cases. Condition coverage is not the same as the decision coverage.

• Path coverage measures coverage in terms of possible paths through a given part of the code executed. 100% path coverage means all possible paths have been executed. A commonly used notation for path analysis is called the Control Flow Graph (CFG).
• Entry/exit coverage measures coverage in terms of possible calls to and exits from the operations in the SUT.

Measuring coverage is often done using coverage analysis tools. Most IDEs have inbuilt support for measuring test coverage, or at least have plugins that can measure test coverage.

Coverage analysis can be useful in improving the quality of testing e.g., if a set of test cases does not achieve 100% branch coverage, more test cases can be added to cover missed branches.

Test-Driven Development(TDD) advocates writing the tests before writing the SUT, while evolving functionality and tests in small increments. In TDD you first define the precise behavior of the SUT using test cases, and then write the SUT to match the specified behavior. While TDD has its fair share of detractors, there are many who consider it a good way to reduce defects. One big advantage of TDD is that it guarantees the code is testable.