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TIC4002 2021 Jan-May
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  • Week 10 [Fri, Mar 19th] - Topics

       Integration Testing

    • [W10.1a] Quality Assurance → Testing → Integration Testing → What :

    • [W10.1b] Quality Assurance → Testing → Integration Testing → How :

       System Testing

    • [W10.1c] Quality Assurance → Testing → System Testing → What :

    • [W10.1d] Quality Assurance → Testing → Test Automation → Automated testing of GUIs :

       Acceptance Testing

    • [W10.1e] Quality Assurance → Testing → Acceptance Testing → What :

    • [W10.1f] Quality Assurance → Testing → Acceptance Testing → Acceptance versus system testing :

       Alpha/Beta Testing

    • [W10.1g] Quality Assurance → Testing → Alpha/Beta Testing → What :

       Exploratory vs Scripted Testing

    • [W10.1h] Quality Assurance → Testing → Exploratory and Scripted Testing → What :

    • [W10.1i] Quality Assurance → Testing → Exploratory and Scripted Testing → When :

    • [W10.2] Testing: Intermediate Concepts

       Dependency Injection

    • [W10.2a] Quality Assurance → Testing → Dependency Injection → What :

    • [W10.2b] Quality Assurance → Testing → Dependency Injection → How :

       Testability

    • [W10.2c] Quality Assurance → Testing → Introduction → Testability :

       Test Coverage

    • [W10.2d] Quality Assurance → Testing → Test Coverage → What :

    • [W10.2e] Quality Assurance → Testing → Test Coverage → How :

       TDD

    • [W10.2f] Quality Assurance → Testing → Test-Driven Development → What :


    [W10.1] Testing: Types


    Integration Testing

    W10.1a :

    Quality Assurance → Testing → Integration Testing → What

    Video

    Can explain integration testing

    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.

    Suppose a class Car uses classes Engine and Wheel. If the Car class assumed a Wheel can support a speed of up to 200 mph but the actual Wheel can only support a speed of up to 150 mph, it is the integration test that is supposed to uncover this discrepancy.

    W10.1b :

    Quality Assurance → Testing → Integration Testing → How

    Video

    Can use integration testing

    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.

    Suppose a class Car uses classes Engine and Wheel. Here is how you would go about doing pure integration tests:

    a) First, unit test Engine and Wheel.
    b) Next, unit test Car in isolation of Engine and Wheel, using stubs for Engine and Wheel.
    c) After that, do an integration test for Car by using it together with the Engine and Wheel classes to ensure that Car integrates properly with the Engine and the Wheel.

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

    Here's how a hybrid unit+integration approach could be applied to the same example used above:

    (a) First, unit test Engine and Wheel.
    (b) Next, unit test Car in isolation of Engine and Wheel, using stubs for Engine and Wheel.
    (c) After that, do an integration test for Car by using it together with the Engine and Wheel classes to ensure that Car integrates properly with the Engine and the Wheel. This step should include test cases that are meant to unit test Car (i.e. test cases used in the step (b) of the example above) as well as test cases that are meant to test the integration of Car with Wheel and Engine (i.e. pure integration test cases used of the step (c) in the example above).

    Note that you no longer need stubs for Engine and Wheel. The downside is that Car is never tested in isolation of its dependencies. Given that its dependencies are already unit tested, the risk of bugs in Engine and Wheel affecting the testing of Car can be considered minimal.


    System Testing

    W10.1c :

    Quality Assurance → Testing → System Testing → What

    Can explain system testing

    System testing: take the whole system and test it against the system specification.

    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.

    Suppose the SUT is a browser that is supposedly capable of handling web pages containing up to 5000 characters. Given below is a test case to test if the SUT fails gracefully if pushed beyond its limits.

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

    This test case would fail if the browser attempted to load the large file anyway and crashed.

    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.

    W10.1d :

    Quality Assurance → Testing → Test Automation → Automated testing of GUIs

    Video

    Can explain automated GUI testing

    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.

    Some tools used for automated GUI testing:

    • TestFX can do automated testing of JavaFX GUIs

    • Visual Studio supports the ‘record replay’ type of GUI test automation.

    • Selenium can be used to automate testing of web application UIs

      This video shows automated testing of the TEAMMATES web app using Selenium.

    GUI testing is usually easier than API testing because it doesn’t require any extra coding.

    False


    Acceptance Testing

    W10.1e :

    Quality Assurance → Testing → Acceptance Testing → What

    Can explain acceptance testing

    Acceptance testing (aka User Acceptance Testing (UAT): test the system to ensure it meets the user requirements.

    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.

    W10.1f :

    Quality Assurance → Testing → Acceptance Testing → Acceptance versus system testing

    Video

    Can explain the differences between system testing and acceptance testing

    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:

    System Testing Acceptance Testing
    Done against the system specification Done against the requirements specification
    Done by testers of the project team Done by a team that represents the customer
    Done on the development environment or a test bed Done on the deployment site or on a close simulation of the deployment site
    Both negative and positive test cases More focus on positive test cases

    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

    Requirement specification versus system specification

    The requirement specification need not be the same as the system specification. Some example differences:

    Requirements specification System specification
    limited to how the system behaves in normal working conditions can also include details on how it will fail gracefully when pushed beyond limits, how to recover, etc. specification
    written in terms of problems that need to be solved (e.g. provide a method to locate an email quickly) written in terms of how the system solves those problems (e.g. explain the email search feature)
    specifies the interface available for intended end-users could contain additional APIs not available for end-users (for the use of developers/testers)

    However, in many cases one document serves as both a requirement specification and a system specification.

    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.

    Choose the correct statements about system testing and acceptance testing.

    • a. Both system testing and acceptance testing typically involve the whole system.
    • b. System testing is typically more extensive than acceptance testing.
    • c. System testing can include testing for non-functional qualities.
    • d. Acceptance testing typically has more user involvement than system testing.
    • e. In smaller projects, the developers may do system testing as well, in addition to developer testing.
    • f. If system testing is adequately done, we need not do acceptance testing.

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

    Explanation:

    (b) is correct because system testing can aim to cover all specified behaviors and can even go beyond the system specification. Therefore, system testing is typically more extensive than acceptance testing.

    (f) is incorrect because it is possible for a system to pass system tests but fail acceptance tests.


    Alpha/Beta Testing

    W10.1g :

    Quality Assurance → Testing → Alpha/Beta Testing → What

    Can explain alpha and beta testing

    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.


    Exploratory vs Scripted Testing

    W10.1h :

    Quality Assurance → Testing → Exploratory and Scripted Testing → What

    Can explain exploratory testing and scripted testing

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

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

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

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

    Here is an example thought process behind a segment of an exploratory testing session:

    “Hmm... looks like feature x is broken. This usually means feature n and k could be broken too; you need to look at them soon. But before that, you should give a good test run to feature y because users can still use the product if feature y works, even if x doesn’t work. Now, if feature y doesn’t work 100%, you have a major problem and this has to be made known to the development team sooner rather than later...”

    Exploratory testing is also known as reactive testing, error guessing technique, attack-based testing, and bug hunting.

    Exploratory Testing Explained, an online article by James Bach -- James Bach is an industry thought leader in software testing.

    Scripted testing requires tests to be written in a scripting language; manual testing is called exploratory testing.

    False

    Explanation: “Scripted” means test cases are predetermined. They need not be an executable script. However, exploratory testing is usually manual.

    Which testing technique is better?

    (e)

    Explain the concept of exploratory testing using Minesweeper as an example.

    When we test Minesweeper by simply playing it in various ways, especially trying out those that are likely to be buggy, that would be exploratory testing.

    W10.1i :

    Quality Assurance → Testing → Exploratory and Scripted Testing → When

    Video

    Can explain the choice between exploratory testing and scripted testing

    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]

    Exploratory Testing Explained, an online article by James Bach -- James Bach is an industry thought leader in software testing.

    Scripted testing is better than exploratory testing.

    False

    Explanation: Each has its pros and cons. Relying on only one is not recommended. A combination is better.

    [W10.2] Testing: Intermediate Concepts


    Dependency Injection

    Video

    W10.2a :

    Quality Assurance → Testing → Dependency Injection → What

    Can explain dependency injection

    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.

    Quality Assurance → Testing → Unit Testing →

    Stubs

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

    If a Logic class depends on a Storage class, unit testing the Logic class requires isolating the Logic class from the Storage class.

    Stubs can isolate the Software Under Test (in this case, the unit being tested)SUT from its dependencies.

    Stub: A stub has the same interface as the component it replaces, but its implementation is so simple that it is unlikely to have any bugs. It mimics the responses of the component, but only for a limited set of predetermined inputs. That is, it does not know how to respond to any other inputs. Typically, these mimicked responses are hard-coded in the stub rather than computed or retrieved from elsewhere, e.g. from a database.

    Consider the code below:

    class Logic {
        Storage s;
    
        Logic(Storage s) {
            this.s = s;
        }
    
        String getName(int index) {
            return "Name: " + s.getName(index);
        }
    }
    
    interface Storage {
        String getName(int index);
    }
    
    class DatabaseStorage implements Storage {
    
        @Override
        public String getName(int index) {
            return readValueFromDatabase(index);
        }
    
        private String readValueFromDatabase(int index) {
            // retrieve name from the database
        }
    }
    

    Normally, you would use the Logic class as follows (note how the Logic object depends on a DatabaseStorage object to perform the getName() operation):

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

    You can test it like this:

    @Test
    void getName() {
        Logic logic = new Logic(new DatabaseStorage());
        assertEquals("Name: John", logic.getName(5));
    }
    

    However, this logic object being tested is making use of a DataBaseStorage object which means a bug in the DatabaseStorage class can affect the test. Therefore, this test is not testing Logic in isolation from its dependencies and hence it is not a pure unit test.

    Here is a stub class you can use in place of DatabaseStorage:

    class StorageStub implements Storage {
    
        @Override
        public String getName(int index) {
            if (index == 5) {
                return "Adam";
            } else {
                throw new UnsupportedOperationException();
            }
        }
    }
    

    Note how the StorageStub has the same interface as DatabaseStorage, but is so simple that it is unlikely to contain bugs, and is pre-configured to respond with a hard-coded response, presumably, the correct response DatabaseStorage is expected to return for the given test input.

    Here is how you can use the stub to write a unit test. This test is not affected by any bugs in the DatabaseStorage class and hence is a pure unit test.

    @Test
    void getName() {
        Logic logic = new Logic(new StorageStub());
        assertEquals("Name: Adam", logic.getName(5));
    }
    

    In addition to Stubs, there are other type of replacements you can use during testing, e.g. Mocks, Fakes, Dummies, Spies.

    • Mocks Aren't Stubs by Martin Fowler -- An in-depth article about how Stubs differ from other types of test helpers.

    Stubs help us to test a component in isolation from its dependencies.

    True

    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.

    W10.2b :

    Quality Assurance → Testing → Dependency Injection → How

    Can use dependency injection

    Polymorphism can be used to implement dependency injection, as can be seen in the example given in [Quality Assurance → Testing → Unit Testing → Stubs] where a stub is injected to replace a dependency.

    Quality Assurance → Testing → Unit Testing →

    Stubs

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

    If a Logic class depends on a Storage class, unit testing the Logic class requires isolating the Logic class from the Storage class.

    Stubs can isolate the Software Under Test (in this case, the unit being tested)SUT from its dependencies.

    Stub: A stub has the same interface as the component it replaces, but its implementation is so simple that it is unlikely to have any bugs. It mimics the responses of the component, but only for a limited set of predetermined inputs. That is, it does not know how to respond to any other inputs. Typically, these mimicked responses are hard-coded in the stub rather than computed or retrieved from elsewhere, e.g. from a database.

    Consider the code below:

    class Logic {
        Storage s;
    
        Logic(Storage s) {
            this.s = s;
        }
    
        String getName(int index) {
            return "Name: " + s.getName(index);
        }
    }
    
    interface Storage {
        String getName(int index);
    }
    
    class DatabaseStorage implements Storage {
    
        @Override
        public String getName(int index) {
            return readValueFromDatabase(index);
        }
    
        private String readValueFromDatabase(int index) {
            // retrieve name from the database
        }
    }
    

    Normally, you would use the Logic class as follows (note how the Logic object depends on a DatabaseStorage object to perform the getName() operation):

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

    You can test it like this:

    @Test
    void getName() {
        Logic logic = new Logic(new DatabaseStorage());
        assertEquals("Name: John", logic.getName(5));
    }
    

    However, this logic object being tested is making use of a DataBaseStorage object which means a bug in the DatabaseStorage class can affect the test. Therefore, this test is not testing Logic in isolation from its dependencies and hence it is not a pure unit test.

    Here is a stub class you can use in place of DatabaseStorage:

    class StorageStub implements Storage {
    
        @Override
        public String getName(int index) {
            if (index == 5) {
                return "Adam";
            } else {
                throw new UnsupportedOperationException();
            }
        }
    }
    

    Note how the StorageStub has the same interface as DatabaseStorage, but is so simple that it is unlikely to contain bugs, and is pre-configured to respond with a hard-coded response, presumably, the correct response DatabaseStorage is expected to return for the given test input.

    Here is how you can use the stub to write a unit test. This test is not affected by any bugs in the DatabaseStorage class and hence is a pure unit test.

    @Test
    void getName() {
        Logic logic = new Logic(new StorageStub());
        assertEquals("Name: Adam", logic.getName(5));
    }
    

    In addition to Stubs, there are other type of replacements you can use during testing, e.g. Mocks, Fakes, Dummies, Spies.

    • Mocks Aren't Stubs by Martin Fowler -- An in-depth article about how Stubs differ from other types of test helpers.

    Stubs help us to test a component in isolation from its dependencies.

    True

    Here is another example of using polymorphism to implement dependency injection:

    Suppose you want to unit test Payroll#totalSalary() given below. The method depends on the SalaryManager object to calculate the return value. Note how the setSalaryManager(SalaryManager) can be used to inject a SalaryManager object to replace the current SalaryManager object.

    class Payroll {
        private SalaryManager manager = new SalaryManager();
        private String[] employees;
    
        void setEmployees(String[] employees) {
            this.employees = employees;
        }
    
        void setSalaryManager(SalaryManager sm) {
            this.manager = sm;
        }
    
        double totalSalary() {
            double total = 0;
            for (int i = 0; i < employees.length; i++) {
                total += manager.getSalaryForEmployee(employees[i]);
            }
            return total;
        }
    }
    
    
    class SalaryManager {
        double getSalaryForEmployee(String empID) {
            // code to access employee’s salary history
            // code to calculate total salary paid and return it
        }
    }
    

    During testing, you can inject a SalaryManagerStub object to replace the SalaryManager object.

    class PayrollTest {
        public static void main(String[] args) {
            // test setup
            Payroll p = new Payroll();
            p.setSalaryManager(new SalaryManagerStub()); // dependency injection
            // test case 1
            p.setEmployees(new String[]{"E001", "E002"});
            assertEquals(2500.0, p.totalSalary());
            // test case 2
            p.setEmployees(new String[]{"E001"});
            assertEquals(1000.0, p.totalSalary());
            // more tests ...
        }
    }
    
    
    class SalaryManagerStub extends SalaryManager {
        /** Returns hard coded values used for testing */
        double getSalaryForEmployee(String empID) {
            if (empID.equals("E001")) {
                return 1000.0;
            } else if (empID.equals("E002")) {
                return 1500.0;
            } else {
                throw new Error("unknown id");
            }
        }
    }
    

    Choose the correct statements about dependency injection.

    • a. It is a technique for increasing dependencies
    • b. It is useful for unit testing
    • c. It can be done using polymorphism
    • d. It can be used to substitute a component with a stub

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

    Explanation: It is a technique we can use to substitute an existing dependency with another, not increase dependencies. It is useful when you want to test a component in isolation but the SUT depends on other components. Using dependency injection, we can substitute those other components with test-friendly stubs. This is often done using polymorphism.


    Testability

    W10.2c :

    Quality Assurance → Testing → Introduction → Testability

    Can explain testability

    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

    Video

    W10.2d :

    Quality Assurance → Testing → Test Coverage → What

    Can explain test coverage

    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.

    if(x > 2 && x < 44) is considered one decision point but two conditions.

    For 100% branch or decision coverage, two test cases are required:

    • (x > 2 && x < 44) == true : [e.g. x == 4]
    • (x > 2 && x < 44) == false : [e.g. x == 100]

    For 100% condition coverage, three test cases are required:

    • (x > 2) == true , (x < 44) == true : [e.g. x == 4]
    • (x < 44) == false : [e.g. x == 100]
    • (x > 2) == false : [e.g. x == 0]
    • 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.

    Which of these gives us the highest intensity of testing?

    (b)

    Explanation: 100% path coverage implies all possible execution paths through the SUT have been tested. This is essentially ‘exhaustive testing’. While this is very hard to achieve for a non-trivial SUT, it technically gives us the highest intensity of testing. If all tests pass at 100% path coverage, the SUT code can be considered ‘bug free’. However, note that path coverage does not include paths that are missing from the code altogether because the programmer left them out by mistake.

    W10.2e :

    Quality Assurance → Testing → Test Coverage → How

    Can explain how test coverage works

    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.

    Measuring code coverage in Intellij IDEA


    TDD

    Video

    W10.2f :

    Quality Assurance → Testing → Test-Driven Development → What

    Can explain TDD

    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.

    A) In TDD, we write all the test cases before we start writing functional code.

    B) Testing tools such as JUnit require us to follow TDD.

    A) False

    Explanation: No, not all. We proceed in small steps, writing tests and functional code in tandem, but writing the test before we write the corresponding functional code.

    B) False

    Explanation: They can be used for TDD, but they can be used without TDD too.