Software Testing methods
Software Testing methods
The box approach
Software testing methods are traditionally divided into black box testing and white box testing. These two approaches are used to describe the point of view that a test engineer takes when designing test cases.
Black box testing
Black box testing treats the software as a “black box”—without any knowledge of internal implementation. Black box testing methods include: equivalence partitioning, boundary value analysis, all-pairs testing, fuzz testing, model-based testing, traceability matrix, exploratory testing and specification-based testing.
Specification-based testing: Specification-based testing aims to test the functionality of software according to the applicable requirements. Thus, the tester inputs data into, and only sees the output from, the test object. This level of testing usually requires thorough test cases to be provided to the tester, who then can simply verify that for a given input, the output value (or behavior), either “is” or “is not” the same as the expected value specified in the test case.
Specification-based testing is necessary, but it is insufficient to guard against certain risks.
Advantages and disadvantages: The black box tester has no “bonds” with the code, and a tester’s perception is very simple: a code must have bugs. Using the principle, “Ask and you shall receive,” black box testers find bugs where programmers do not. But, on the other hand, black box testing has been said to be “like a walk in a dark labyrinth without a flashlight,” because the tester doesn’t know how the software being tested was actually constructed. As a result, there are situations when (1) a tester writes many test cases to check something that could have been tested by only one test case, and/or (2) some parts of the back-end are not tested at all.
Therefore, black box testing has the advantage of “an unaffiliated opinion,” on the one hand, and the disadvantage of “blind exploring,” on the other.
White box testing
White box testing is when the tester has access to the internal data structures and algorithms including the code that implement these.
Types of white box testing
The following types of white box testing exist:
· API testing (application programming interface) – Testing of the application using Public and Private APIs
· Code coverage – creating tests to satisfy some criteria of code coverage (e.g., the test designer can create tests to cause all statements in the program to be executed at least once)
· Fault injection methods – improving the coverage of a test by introducing faults to test code paths
· Mutation testing methods
· Static testing – White box testing includes all static testing
White box testing methods can also be used to evaluate the completeness of a test suite that was created with black box testing methods. This allows the software team to examine parts of a system that are rarely tested and ensures that the most important function points have been tested.
Two common forms of code coverage are:
· Function coverage, which reports on functions executed
· Statement coverage, which reports on the number of lines executed to complete the test
They both return a code coverage metric, measured as a percentage.
Grey Box Testing
Grey box testing (American spelling: Gray box testing) involves having access to internal data structures and algorithms for purposes of designing the test cases, but testing at the user, or black-box level. Manipulating input data and formatting output do not qualify as grey box, because the input and output are clearly outside of the “black-box” that we are calling the system under test. This distinction is particularly important when conducting integration testing between two modules of code written by two different developers, where only the interfaces are exposed for test. However, modifying a data repository does qualify as grey box, as the user would not normally be able to change the data outside of the system under test. Grey box testing may also include reverse engineering to determine, for instance, boundary values or error messages.
Tests are frequently grouped by where they are added in the software development process, or by the level of specificity of the test.
Unit testing refers to tests that verify the functionality of a specific section of code, usually at the function level. In an object-oriented environment, this is usually at the class level, and the minimal unit tests include the constructors and destructors.
These type of tests are usually written by developers as they work on code (white-box style), to ensure that the specific function is working as expected. One function might have multiple tests, to catch corner cases or other branches in the code. Unit testing alone cannot verify the functionality of a piece of software, but rather is used to assure that the building blocks the software uses work independently of each other.
Unit testing is also called Component Testing.
Integration testing is any type of software testing that seeks to verify the interfaces between components against a software design. Software components may be integrated in an iterative way or all together (“big bang”). Normally the former is considered a better practice since it allows interface issues to be localised more quickly and fixed.
Integration testing works to expose defects in the interfaces and interaction between integrated components (modules). Progressively larger groups of tested software components corresponding to elements of the architectural design are integrated and tested until the software works as a system.
System testing tests a completely integrated system to verify that it meets its requirements.
System Integration Testing
System integration testing verifies that a system is integrated to any external or third party systems defined in the system requirements.
Regression testing focuses on finding defects after a major code change has occurred. Specifically, it seeks to uncover software regressions, or old bugs that have come back. Such regressions occur whenever software functionality that was previously working correctly stops working as intended. Typically, regressions occur as an unintended consequence of program changes, when the newly developed part of the software collides with the previously existing code. Common methods of regression testing include re-running previously run tests and checking whether previously fixed faults have re-emerged. The depth of testing depends on the phase in the release process and the risk of the added features. They can either be complete, for changes added late in the release or deemed to be risky, to very shallow, consisting of positive tests on each feature, if the changes are early in the release or deemed to be of low risk.
Acceptance testing can mean one of two things:
A smoke test is used as an acceptance test prior to introducing a new build to the main testing process, i.e. before integration or regression.
Acceptance testing performed by the customer, often in their lab environment on their own HW, is known as user acceptance testing (UAT). Acceptance testing may be performed as part of the hand-off process between any two phases of development.
Alpha testing is simulated or actual operational testing by potential users/customers or an independent test team at the developers’ site. Alpha testing is often employed for off-the-shelf software as a form of internal acceptance testing, before the software goes to beta testing.
Beta testing comes after alpha testing. Versions of the software, known as beta versions, are released to a limited audience outside of the programming team. The software is released to groups of people so that further testing can ensure the product has few faults or bugs. Sometimes, beta versions are made available to the open public to increase the feedback field to a maximal number of future users.
Non Functional Software Testing
Special methods exist to test non-functional aspects of software. In contrast to functional testing, which establishes the correct operation of the software (correct in that it matches the expected behavior defined in the design requirements), non-functional testing verifies that the software functions properly even when it receives invalid or unexpected inputs. Software fault injection, in the form of fuzzing, is an example of non-functional testing. Non-functional testing, especially for software, is designed to establish whether the device under test can tolerate invalid or unexpected inputs, thereby establishing the robustness of input validation routines as well as error-handling routines. Various commercial non-functional testing tools are linked from the Software fault injection page; there are also numerous open-source and free software tools available that perform non-functional testing.
Software performance testing and load testing
Performance testing is executed to determine how fast a system or sub-system performs under a particular workload. It can also serve to validate and verify other quality attributes of the system, such as scalability, reliability and resource usage. Load testing is primarily concerned with testing that can continue to operate under a specific load, whether that be large quantities of data or a large number of users. This is generally referred to as software scalability. The related load testing activity of when performed as a non-functional activity is often referred to as Endurance Testing.
Volume testing is a way to test functionality. Stress testing is a way to test reliability. Load testing is a way to test performance. There is little agreement on what the specific goals of load testing are. The terms load testing, performance testing, reliability testing, and volume testing, are often used interchangeably.
Stability testing checks to see if the software can continuously function well in or above an acceptable period. This activity of Non Functional Software Testing is oftentimes referred to as load (or endurance) testing.
Usability testing is needed to check if the user interface is easy to use and understand.
Security testing is essential for software that processes confidential data to prevent system intrusion by hackers.
Internationalization and localization
Internationalization and localization is needed to test these aspects of software, for which a pseudolocalization method can be used. It will verify that the application still works, even after it has been translated into a new language or adapted for a new culture (such as different currencies or time zones).
Destructive testing attempts to cause the software or a sub-system to fail, in order to test its robustness.
The testing process
Traditional CMMI or waterfall development model
A common practice of software testing is that testing is performed by an independent group of testers after the functionality is developed, before it is shipped to the customer. This practice often results in the testing phase being used as a project buffer to compensate for project delays, thereby compromising the time devoted to testing.
Another practice is to start software testing at the same moment the project starts and it is a continuous process until the project finishes.
Agile or Extreme development model
In counterpoint, some emerging software disciplines such as extreme programming and the agile software development movement, adhere to a “test-driven software development” model. In this process, unit tests are written first, by the software engineers (often with pair programming in the extreme programming methodology). Of course these tests fail initially; as they are expected to. Then as code is written it passes incrementally larger portions of the test suites. The test suites are continuously updated as new failure conditions and corner cases are discovered, and they are integrated with any regression tests that are developed. Unit tests are maintained along with the rest of the software source code and generally integrated into the build process (with inherently interactive tests being relegated to a partially manual build acceptance process). The ultimate goal of this test process is to achieve continuous deployment where software updates can be published to the public frequently.
A sample testing cycle
Although variations exist between organizations, there is a typical cycle for testing. The sample below is common among organizations employing the Waterfall development model.
Requirements analysis: Testing should begin in the requirements phase of the software development life cycle. During the design phase, testers work with developers in determining what aspects of a design are testable and with what parameters those tests work.
Test planning: Test strategy, test plan, testbed creation. Since many activities will be carried out during testing, a plan is needed.
Test development: Test procedures, test scenarios, test cases, test datasets, test scripts to use in testing software.
Test execution: Testers execute the software based on the plans and tests and report any errors found to the development team.
Test reporting: Once testing is completed, testers generate metrics and make final reports on their test effort and whether or not the software tested is ready for release.
Test result analysis: Or Defect Analysis, is done by the development team usually along with the client, in order to decide what defects should be treated, fixed, rejected (i.e. found software working properly) or deferred to be dealt with later.
Defect Retesting: Once a defect has been dealt with by the development team, it is retested by the testing team. AKA Resolution testing.
Regression testing: It is common to have a small test program built of a subset of tests, for each integration of new, modified, or fixed software, in order to ensure that the latest delivery has not ruined anything, and that the software product as a whole is still working correctly.
Test Closure: Once the test meets the exit criteria, the activities such as capturing the key outputs, lessons learned, results, logs, documents related to the project are archived and used as a reference for future projects.
Many programming groups are relying more and more on automated testing, especially groups that use Test-driven development. There are many frameworks to write tests in, and Continuous Integration software will run tests automatically every time code is checked into a version control system.
While automation cannot reproduce everything that a human can do (and all the strange ways they think of to do it), it can be very useful for regression testing. However, it does require a well-developed test suite of testing scripts in order to be truly useful.
Program testing and fault detection can be aided significantly by testing tools and debuggers. Testing/debug tools include features such as:
Program monitors, permitting full or partial monitoring of program code including:
Instruction Set Simulator, permitting complete instruction level monitoring and trace facilities
Program animation, permitting step-by-step execution and conditional breakpoint at source level or in machine code
Code coverage reports
Formatted dump or Symbolic debugging, tools allowing inspection of program variables on error or at chosen points
Automated functional GUI testing tools are used to repeat system-level tests through the GUI
Benchmarks, allowing run-time performance comparisons to be made
Performance analysis (or profiling tools) that can help to highlight hot spots and resource usage
Some of these features may be incorporated into an Integrated Development Environment (IDE).
Measuring software testing
Usually, quality is constrained to such topics as correctness, completeness, security, but can also include more technical requirements as described under the ISO standard ISO 9126, such as capability, reliability, efficiency, portability, maintainability, compatibility, and
There are a number of common software measures, often called “metrics”, which are used to measure the state of the software or the adequacy of the testing.
Software testing process can produce several artifacts.
A test specification is called a test plan. The developers are well aware what test plans will be executed and this information is made available to management and the developers. The idea is to make them more cautious when developing their code or making additional changes. Some companies have a higher-level document called a test strategy.
A traceability matrix is a table that correlates requirements or design documents to test documents. It is used to change tests when the source documents are changed, or to verify that the test results are correct.
A test case normally consists of a unique identifier, requirement references from a design specification, preconditions, events, a series of steps (also known as actions) to follow, input, output, expected result, and actual result. Clinically defined a test case is an input and an expected result. This can be as pragmatic as ‘for condition x your derived result is y’, whereas other test cases described in more detail the input scenario and what results might be expected. It can occasionally be a series of steps (but often steps are contained in a separate test procedure that can be exercised against multiple test cases, as a matter of economy) but with one expected result or expected outcome. The optional fields are a test case ID, test step, or order of execution number, related requirement(s), depth, test category, author, and check boxes for whether the test is automatable and has been automated. Larger test cases may also contain prerequisite states or steps, and descriptions. A test case should also contain a place for the actual result. These steps can be stored in a word processor document, spreadsheet, database, or other common repository. In a database system, you may also be able to see past test results, who generated the results, and what system configuration was used to generate those results. These past results would usually be stored in a separate table.
The test script is the combination of a test case, test procedure, and test data. Initially the term was derived from the product of work created by automated regression test tools. Today, test scripts can be manual, automated, or a combination of both.
The most common term for a collection of test cases is a test suite. The test suite often also contains more detailed instructions or goals for each collection of test cases. It definitely contains a section where the tester identifies the system configuration used during testing. A group of test cases may also contain prerequisite states or steps, and descriptions of the following tests.
In most cases, multiple sets of values or data are used to test the same functionality of a particular feature. All the test values and changeable environmental components are collected in separate files and stored as test data. It is also useful to provide this data to the client and with the product or a project.
The software, tools, samples of data input and output, and configurations are all referred to collectively as a test harness.