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Test-driven development

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Test-driven development (TDD) is a software development process relying on software requirements being converted to test cases before software is fully developed, and tracking all software development by repeatedly testing the software against all test cases. This is as opposed to software being developed first and test cases created later.

Software engineer Kent Beck, who is credited with having developed or "rediscovered"[1] the technique, stated in 2003 that TDD encourages simple designs and inspires confidence.[2]

Test-driven development is related to the test-first programming concepts of extreme programming, begun in 1999,[3] but more recently has created more general interest in its own right.[4]

Programmers also apply the concept to improving and debugging legacy code developed with older techniques.[5]

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Software development process

Software development process

In software engineering, a software development process is a process of dividing software development work into smaller, parallel, or sequential steps or sub-processes to improve design, product management. It is also known as a software development life cycle (SDLC). The methodology may include the pre-definition of specific deliverables and artifacts that are created and completed by a project team to develop or maintain an application.

Test case

Test case

In software engineering, a test case is a specification of the inputs, execution conditions, testing procedure, and expected results that define a single test to be executed to achieve a particular software testing objective, such as to exercise a particular program path or to verify compliance with a specific requirement. Test cases underlie testing that is methodical rather than haphazard. A battery of test cases can be built to produce the desired coverage of the software being tested. Formally defined test cases allow the same tests to be run repeatedly against successive versions of the software, allowing for effective and consistent regression testing.

Kent Beck

Kent Beck

Kent Beck is an American software engineer and the creator of extreme programming, a software development methodology that eschews rigid formal specification for a collaborative and iterative design process. Beck was one of the 17 original signatories of the Agile Manifesto, the founding document for agile software development. Extreme and Agile methods are closely associated with Test-Driven Development (TDD), of which Beck is perhaps the leading proponent.

Extreme programming

Extreme programming

Extreme programming (XP) is a software development methodology intended to improve software quality and responsiveness to changing customer requirements. As a type of agile software development, it advocates frequent releases in short development cycles, intended to improve productivity and introduce checkpoints at which new customer requirements can be adopted.

Software bug

Software bug

A software bug is an error, flaw or fault in the design, development, or operation of computer software that causes it to produce an incorrect or unexpected result, or to behave in unintended ways. The process of finding and correcting bugs is termed "debugging" and often uses formal techniques or tools to pinpoint bugs. Since the 1950s some computer systems have been designed to deter, detect or auto-correct various computer bugs during operations.

Test-driven development cycle

A graphical representation of the test-driven development lifecycle
A graphical representation of the test-driven development lifecycle

The following sequence is based on the book Test-Driven Development by Example:[2]

1. Add a test
The adding of a new feature begins by writing a test that passes iff the feature's specifications are met. The developer can discover these specifications by asking about use cases and user stories. A key benefit of test-driven development is that it makes the developer focus on requirements before writing code. This is in contrast with the usual practice, where unit tests are only written after code.
2. Run all tests. The new test should fail for expected reasons
This shows that new code is actually needed for the desired feature. It validates that the test harness is working correctly. It rules out the possibility that the new test is flawed and will always pass.
3. Write the simplest code that passes the new test
Inelegant or hard code is acceptable, as long as it passes the test. The code will be honed anyway in Step 5. No code should be added beyond the tested functionality.
4. All tests should now pass
If any fail, the new code must be revised until they pass. This ensures the new code meets the test requirements and does not break existing features.
5. Refactor as needed, using tests after each refactor to ensure that functionality is preserved
Code is refactored for readability and maintainability. In particular, hard-coded test data should be removed. Running the test suite after each refactor helps ensure that no existing functionality is broken.
Repeat
The cycle above is repeated for each new piece of functionality. Tests should be small and incremental, and commits made often. That way, if new code fails some tests, the programmer can simply undo or revert rather than debug excessively. When using external libraries, it is important not to write tests that are so small as to effectively test merely the library itself,[4] unless there is some reason to believe that the library is buggy or not feature-rich enough to serve all the needs of the software under development.

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Use case

Use case

In software and systems engineering, the phrase use case is a polyseme with two senses:A usage scenario for a piece of software; often used in the plural to suggest situations where a piece of software may be useful. A potential scenario in which a system receives an external request and responds to it.

User story

User story

In software development and product management, a user story is an informal, natural language description of features of a software system. They are written from the perspective of an end user or user of a system, and may be recorded on index cards, Post-it notes, or digitally in project management software. Depending on the project, user stories may be written by different stakeholders like client, user, manager, or development team.

Test harness

Test harness

In software testing, a test harness or automated test framework is a collection of software and test data configured to test a program unit by running it under varying conditions and monitoring its behavior and outputs. It has two main parts: the test execution engine and the test script repository.

Software requirements

Software requirements

Software requirements for a system are the description of what the system should do, the service or services that it provides and the constraints on its operation. The IEEE Standard Glossary of Software Engineering Terminology defines a requirement as:A condition or capability needed by a user to solve a problem or achieve an objective. A condition or capability that must be met or possessed by a system or system component to satisfy a contract, standard, specification, or other formally imposed document. A documented representation of a condition or capability as in 1 or 2.

Code refactoring

Code refactoring

In computer programming and software design, code refactoring is the process of restructuring existing computer code—changing the factoring—without changing its external behavior. Refactoring is intended to improve the design, structure, and/or implementation of the software, while preserving its functionality. Potential advantages of refactoring may include improved code readability and reduced complexity; these can improve the source code's maintainability and create a simpler, cleaner, or more expressive internal architecture or object model to improve extensibility. Another potential goal for refactoring is improved performance; software engineers face an ongoing challenge to write programs that perform faster or use less memory.

Duplicate code

Duplicate code

In computer programming, duplicate code is a sequence of source code that occurs more than once, either within a program or across different programs owned or maintained by the same entity. Duplicate code is generally considered undesirable for a number of reasons. A minimum requirement is usually applied to the quantity of code that must appear in a sequence for it to be considered duplicate rather than coincidentally similar. Sequences of duplicate code are sometimes known as code clones or just clones, the automated process of finding duplications in source code is called clone detection.

Name

Name

A name is a term used for identification by an external observer. They can identify a class or category of things, or a single thing, either uniquely, or within a given context. The entity identified by a name is called its referent. A personal name identifies, not necessarily uniquely, a specific individual human. The name of a specific entity is sometimes called a proper name and is, when consisting of only one word, a proper noun. Other nouns are sometimes called "common names" or (obsolete) "general names". A name can be given to a person, place, or thing; for example, parents can give their child a name or a scientist can give an element a name.

Self-documenting code

Self-documenting code

In computer programming, self-documenting source code and user interfaces follow naming conventions and structured programming conventions that enable use of the system without prior specific knowledge. In web development, self-documenting refers to a website that exposes the entire process of its creation through public documentation, and whose public documentation is part of the development process.

Inheritance (object-oriented programming)

Inheritance (object-oriented programming)

In object-oriented programming, inheritance is the mechanism of basing an object or class upon another object or class, retaining similar implementation. Also defined as deriving new classes from existing ones such as super class or base class and then forming them into a hierarchy of classes. In most class-based object-oriented languages, an object created through inheritance, a "child object", acquires all the properties and behaviors of the "parent object", with the exception of: constructors, destructor, overloaded operators and friend functions of the base class. Inheritance allows programmers to create classes that are built upon existing classes, to specify a new implementation while maintaining the same behaviors, to reuse code and to independently extend original software via public classes and interfaces. The relationships of objects or classes through inheritance give rise to a directed acyclic graph.

Undo

Undo

Undo is an interaction technique which is implemented in many computer programs. It erases the last change done to the document, reverting it to an older state. In some more advanced programs, such as graphic processing, undo will negate the last command done to the file being edited. With the possibility of undo, users can explore and work without fear of making mistakes, because they can easily be undone.

Library (computing)

Library (computing)

In computer science, a library is a collection of non-volatile resources used by computer programs, often for software development. These may include configuration data, documentation, help data, message templates, pre-written code and subroutines, classes, values or type specifications. In IBM's OS/360 and its successors they are referred to as partitioned data sets.

Development style

There are various aspects to using test-driven development, for example the principles of "keep it simple, stupid" (KISS) and "You aren't gonna need it" (YAGNI). By focusing on writing only the code necessary to pass tests, designs can often be cleaner and clearer than is achieved by other methods.[2] In Test-Driven Development by Example, Kent Beck also suggests the principle "Fake it till you make it".

To achieve some advanced design concept such as a design pattern, tests are written that generate that design. The code may remain simpler than the target pattern, but still pass all required tests. This can be unsettling at first but it allows the developer to focus only on what is important.

Writing the tests first: The tests should be written before the functionality that is to be tested. This has been claimed to have many benefits. It helps ensure that the application is written for testability, as the developers must consider how to test the application from the outset rather than adding it later. It also ensures that tests for every feature get written. Additionally, writing the tests first leads to a deeper and earlier understanding of the product requirements, ensures the effectiveness of the test code, and maintains a continual focus on software quality.[6] When writing feature-first code, there is a tendency by developers and organizations to push the developer on to the next feature, even neglecting testing entirely. The first TDD test might not even compile at first, because the classes and methods it requires may not yet exist. Nevertheless, that first test functions as the beginning of an executable specification.[7]

Each test case fails initially: This ensures that the test really works and can catch an error. Once this is shown, the underlying functionality can be implemented. This has led to the "test-driven development mantra", which is "red/green/refactor", where red means fail and green means pass. Test-driven development constantly repeats the steps of adding test cases that fail, passing them, and refactoring. Receiving the expected test results at each stage reinforces the developer's mental model of the code, boosts confidence and increases productivity.

Keep the unit small

For TDD, a unit is most commonly defined as a class, or a group of related functions often called a module. Keeping units relatively small is claimed to provide critical benefits, including:

  • Reduced debugging effort – When test failures are detected, having smaller units aids in tracking down errors.
  • Self-documenting tests – Small test cases are easier to read and to understand.[6]

Advanced practices of test-driven development can lead to acceptance test–driven development (ATDD) and specification by example where the criteria specified by the customer are automated into acceptance tests, which then drive the traditional unit test-driven development (UTDD) process.[8] This process ensures the customer has an automated mechanism to decide whether the software meets their requirements. With ATDD, the development team now has a specific target to satisfy – the acceptance tests – which keeps them continuously focused on what the customer really wants from each user story.

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KISS principle

KISS principle

KISS, an acronym for "Keep it simple, stupid!", is a design principle noted by the U.S. Navy in 1960. First seen partly in American English by at least 1938, the KISS principle states that most systems work best if they are kept simple rather than made complicated; therefore, simplicity should be a key goal in design, and unnecessary complexity should be avoided. The phrase has been associated with aircraft engineer Kelly Johnson. The term "KISS principle" was in popular use by 1970. Variations on the phrase include "keep it super simple", "keep it simple, silly", "keep it short and simple", "keep it short and sweet", "keep it simple and straightforward", "keep it small and simple", "keep it simple, soldier", "keep it simple, sailor", "keep it simple, sweetie", or "keep it sweet and simple".

You aren't gonna need it

You aren't gonna need it

"You aren't gonna need it" (YAGNI) is a principle which arose from extreme programming (XP) that states a programmer should not add functionality until deemed necessary. Other forms of the phrase include "You aren't going to need it" (YAGTNI) and "You ain't gonna need it" (YAGNI).

Fake it till you make it

Fake it till you make it

"Fake it till you make it" is an English aphorism which suggests that by imitating confidence, competence, and an optimistic mindset, a person can realize those qualities in their real life and achieve the results they seek.

Design pattern

Design pattern

A design pattern is the re-usable form of a solution to a design problem. The idea was introduced by the architect Christopher Alexander and has been adapted for various other disciplines, particularly software engineering.

Software quality

Software quality

In the context of software engineering, software quality refers to two related but distinct notions:Software functional quality reflects how well it complies with or conforms to a given design, based on functional requirements or specifications. That attribute can also be described as the fitness for purpose of a piece of software or how it compares to competitors in the marketplace as a worthwhile product. It is the degree to which the correct software was produced. Software structural quality refers to how it meets non-functional requirements that support the delivery of the functional requirements, such as robustness or maintainability. It has a lot more to do with the degree to which the software works as needed.

Acceptance test–driven development

Acceptance test–driven development

Acceptance test–driven development (ATDD) is a development methodology based on communication between the business customers, the developers, and the testers. ATDD encompasses many of the same practices as specification by example (SBE), behavior-driven development (BDD), example-driven development (EDD), and support-driven development also called story test–driven development (SDD). All these processes aid developers and testers in understanding the customer's needs prior to implementation and allow customers to be able to converse in their own domain language.

Specification by example

Specification by example

Specification by example (SBE) is a collaborative approach to defining requirements and business-oriented functional tests for software products based on capturing and illustrating requirements using realistic examples instead of abstract statements. It is applied in the context of agile software development methods, in particular behavior-driven development. This approach is particularly successful for managing requirements and functional tests on large-scale projects of significant domain and organisational complexity.

Best practices

Test structure

Effective layout of a test case ensures all required actions are completed, improves the readability of the test case, and smooth's the flow of execution. Consistent structure helps in building a self-documenting test case. A commonly applied structure for test cases has (1) setup, (2) execution, (3) validation, and (4) cleanup.

  • Setup: Put the Unit Under Test (UUT) or the overall test system in the state needed to run the test.
  • Execution: Trigger/drive the UUT to perform the target behavior and capture all output, such as return values and output parameters. This step is usually very simple.
  • Validation: Ensure the results of the test are correct. These results may include explicit outputs captured during execution or state changes in the UUT.
  • Cleanup: Restore the UUT or the overall test system to the pre-test state. This restoration permits another test to execute immediately after this one. In some cases, in order to preserve the information for possible test failure analysis, the cleanup should be starting the test just before the test's setup run. [6]

Individual best practices

Some best practices that an individual could follow would be to separate common set-up and tear-down logic into test support services utilized by the appropriate test cases, to keep each test oracle focused on only the results necessary to validate its test, and to design time-related tests to allow tolerance for execution in non-real time operating systems. The common practice of allowing a 5-10 percent margin for late execution reduces the potential number of false negatives in test execution. It is also suggested to treat test code with the same respect as production code. Test code must work correctly for both positive and negative cases, last a long time, and be readable and maintainable. Teams can get together with and review tests and test practices to share effective techniques and catch bad habits.[9]

Practices to avoid, or "anti-patterns"

  • Having test cases depend on system state manipulated from previously executed test cases (i.e., you should always start a unit test from a known and pre-configured state).
  • Dependencies between test cases. A test suite where test cases are dependent upon each other is brittle and complex. Execution order should not be presumed. Basic refactoring of the initial test cases or structure of the UUT causes a spiral of increasingly pervasive impacts in associated tests.
  • Interdependent tests. Interdependent tests can cause cascading false negatives. A failure in an early test case breaks a later test case even if no actual fault exists in the UUT, increasing defect analysis and debug efforts.
  • Testing precise execution, behavior, timing or performance.
  • Building "all-knowing oracles". An oracle that inspects more than necessary is more expensive and brittle over time. This very common error is dangerous because it causes a subtle but pervasive time sink across the complex project.[9]
  • Testing implementation details.
  • Slow running tests.

Benefits

A 2005 study found that using TDD meant writing more tests and, in turn, programmers who wrote more tests tended to be more productive.[10] Hypotheses relating to code quality and a more direct correlation between TDD and productivity were inconclusive.[11]

Programmers using pure TDD on new ("greenfield") projects reported they only rarely felt the need to invoke a debugger. Used in conjunction with a version control system, when tests fail unexpectedly, reverting the code to the last version that passed all tests may often be more productive than debugging.[12]

Test-driven development offers more than just simple validation of correctness, but can also drive the design of a program.[13] By focusing on the test cases first, one must imagine how the functionality is used by clients (in the first case, the test cases). So, the programmer is concerned with the interface before the implementation. This benefit is complementary to design by contract as it approaches code through test cases rather than through mathematical assertions or preconceptions.

Test-driven development offers the ability to take small steps when required. It allows a programmer to focus on the task at hand as the first goal is to make the test pass. Exceptional cases and error handling are not considered initially, and tests to create these extraneous circumstances are implemented separately. Test-driven development ensures in this way that all written code is covered by at least one test. This gives the programming team, and subsequent users, a greater level of confidence in the code.

While it is true that more code is required with TDD than without TDD because of the unit test code, the total code implementation time could be shorter based on a model by Müller and Padberg.[14] Large numbers of tests help to limit the number of defects in the code. The early and frequent nature of the testing helps to catch defects early in the development cycle, preventing them from becoming endemic and expensive problems. Eliminating defects early in the process usually avoids lengthy and tedious debugging later in the project.

TDD can lead to more modularized, flexible, and extensible code. This effect often comes about because the methodology requires that the developers think of the software in terms of small units that can be written and tested independently and integrated together later. This leads to smaller, more focused classes, looser coupling, and cleaner interfaces. The use of the mock object design pattern also contributes to the overall modularization of the code because this pattern requires that the code be written so that modules can be switched easily between mock versions for unit testing and "real" versions for deployment.

Because no more code is written than necessary to pass a failing test case, automated tests tend to cover every code path. For example, for a TDD developer to add an else branch to an existing if statement, the developer would first have to write a failing test case that motivates the branch. As a result, the automated tests resulting from TDD tend to be very thorough: they detect any unexpected changes in the code's behaviour. This detects problems that can arise where a change later in the development cycle unexpectedly alters other functionality.

Madeyski[15] provided empirical evidence (via a series of laboratory experiments with over 200 developers) regarding the superiority of the TDD practice over the traditional Test-Last approach or testing for correctness approach, with respect to the lower coupling between objects (CBO). The mean effect size represents a medium (but close to large) effect on the basis of meta-analysis of the performed experiments which is a substantial finding. It suggests a better modularization (i.e., a more modular design), easier reuse and testing of the developed software products due to the TDD programming practice.[15] Madeyski also measured the effect of the TDD practice on unit tests using branch coverage (BC) and mutation score indicator (MSI),[16][17][18] which are indicators of the thoroughness and the fault detection effectiveness of unit tests, respectively. The effect size of TDD on branch coverage was medium in size and therefore is considered substantive effect.[15] These findings have been subsequently confirmed by further, smaller experimental evaluations of TDD.[19][20][21][22]

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Greenfield project

Greenfield project

In many disciplines, a greenfield project is one that lacks constraints imposed by prior work. The analogy is to that of construction on greenfield land where there is no need to work within the constraints of existing buildings or infrastructure.

Debugger

Debugger

A debugger or debugging tool is a computer program used to test and debug other programs. The main use of a debugger is to run the target program under controlled conditions that permit the programmer to track its execution and monitor changes in computer resources that may indicate malfunctioning code. Typical debugging facilities include the ability to run or halt the target program at specific points, display the contents of memory, CPU registers or storage devices, and modify memory or register contents in order to enter selected test data that might be a cause of faulty program execution.

Design by contract

Design by contract

Design by contract (DbC), also known as contract programming, programming by contract and design-by-contract programming, is an approach for designing software.

Coupling (computer programming)

Coupling (computer programming)

In software engineering, coupling is the degree of interdependence between software modules; a measure of how closely connected two routines or modules are; the strength of the relationships between modules.

Mock object

Mock object

In object-oriented programming, mock objects are simulated objects that mimic the behaviour of real objects in controlled ways, most often as part of a software testing initiative. A programmer typically creates a mock object to test the behaviour of some other object, in much the same way that a car designer uses a crash test dummy to simulate the dynamic behaviour of a human in vehicle impacts. The technique is also applicable in generic programming.

Limitations

Test-driven development does not perform sufficient testing in situations where full functional tests are required to determine success or failure, due to extensive use of unit tests.[23] Examples of these are user interfaces, programs that work with databases, and some that depend on specific network configurations. TDD encourages developers to put the minimum amount of code into such modules and to maximize the logic that is in testable library code, using fakes and mocks to represent the outside world.[24]

Management support is essential. Without the entire organization believing that test-driven development is going to improve the product, management may feel that time spent writing tests is wasted.[25]

Unit tests created in a test-driven development environment are typically created by the developer who is writing the code being tested. Therefore, the tests may share blind spots with the code: if, for example, a developer does not realize that certain input parameters must be checked, most likely neither the test nor the code will verify those parameters. Another example: if the developer misinterprets the requirements for the module they are developing, the code and the unit tests they write will both be wrong in the same way. Therefore, the tests will pass, giving a false sense of correctness.

A high number of passing unit tests may bring a false sense of security, resulting in fewer additional software testing activities, such as integration testing and compliance testing.

Tests become part of the maintenance overhead of a project. Badly written tests, for example ones that include hard-coded error strings, are themselves prone to failure, and they are expensive to maintain. This is especially the case with fragile tests.[26] There is a risk that tests that regularly generate false failures will be ignored, so that when a real failure occurs, it may not be detected. It is possible to write tests for low and easy maintenance, for example by the reuse of error strings, and this should be a goal during the code refactoring phase described above.

Writing and maintaining an excessive number of tests costs time. Also, more-flexible modules (with limited tests) might accept new requirements without the need for changing the tests. For those reasons, testing for only extreme conditions, or a small sample of data, can be easier to adjust than a set of highly detailed tests.

The level of coverage and testing detail achieved during repeated TDD cycles cannot easily be re-created at a later date. Therefore, these original, or early, tests become increasingly precious as time goes by. The tactic is to fix it early. Also, if a poor architecture, a poor design, or a poor testing strategy leads to a late change that makes dozens of existing tests fail, then it is important that they are individually fixed. Merely deleting, disabling or rashly altering them can lead to undetectable holes in the test coverage.

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User interface

User interface

In the industrial design field of human–computer interaction, a user interface (UI) is the space where interactions between humans and machines occur. The goal of this interaction is to allow effective operation and control of the machine from the human end, while the machine simultaneously feeds back information that aids the operators' decision-making process. Examples of this broad concept of user interfaces include the interactive aspects of computer operating systems, hand tools, heavy machinery operator controls, and process controls. The design considerations applicable when creating user interfaces are related to, or involve such disciplines as, ergonomics and psychology.

Database

Database

In computing, a database is an organized collection of data stored and accessed electronically. Small databases can be stored on a file system, while large databases are hosted on computer clusters or cloud storage. The design of databases spans formal techniques and practical considerations, including data modeling, efficient data representation and storage, query languages, security and privacy of sensitive data, and distributed computing issues, including supporting concurrent access and fault tolerance.

Computer network

Computer network

A computer network is a set of computers sharing resources located on or provided by network nodes. The computers use common communication protocols over digital interconnections to communicate with each other. These interconnections are made up of telecommunication network technologies, based on physically wired, optical, and wireless radio-frequency methods that may be arranged in a variety of network topologies.

Mock object

Mock object

In object-oriented programming, mock objects are simulated objects that mimic the behaviour of real objects in controlled ways, most often as part of a software testing initiative. A programmer typically creates a mock object to test the behaviour of some other object, in much the same way that a car designer uses a crash test dummy to simulate the dynamic behaviour of a human in vehicle impacts. The technique is also applicable in generic programming.

Software testing

Software testing

Software testing is the act of examining the artifacts and the behavior of the software under test by validation and verification. Software testing can also provide an objective, independent view of the software to allow the business to appreciate and understand the risks of software implementation. Test techniques include, but not necessarily limited to:analyzing the product requirements for completeness and correctness in various contexts like industry perspective, business perspective, feasibility and viability of implementation, usability, performance, security, infrastructure considerations, etc. reviewing the product architecture and the overall design of the product working with product developers on improvement in coding techniques, design patterns, tests that can be written as part of code based on various techniques like boundary conditions, etc. executing a program or application with the intent of examining behavior reviewing the deployment infrastructure and associated scripts and automation take part in production activities by using monitoring and observability techniques

Integration testing

Integration testing

Integration testing is the phase in software testing in which individual software modules are combined and tested as a group. Integration testing is conducted to evaluate the compliance of a system or component with specified functional requirements. It occurs after unit testing and before system testing. Integration testing takes as its input modules that have been unit tested, groups them in larger aggregates, applies tests defined in an integration test plan to those aggregates, and delivers as its output the integrated system ready for system testing.

Code refactoring

Code refactoring

In computer programming and software design, code refactoring is the process of restructuring existing computer code—changing the factoring—without changing its external behavior. Refactoring is intended to improve the design, structure, and/or implementation of the software, while preserving its functionality. Potential advantages of refactoring may include improved code readability and reduced complexity; these can improve the source code's maintainability and create a simpler, cleaner, or more expressive internal architecture or object model to improve extensibility. Another potential goal for refactoring is improved performance; software engineers face an ongoing challenge to write programs that perform faster or use less memory.

Test-driven work

Test-driven development has been adopted outside of software development, in both product and service teams, as test-driven work.[27] For testing to be successful, it needs to be practiced at the micro and macro levels. Every method in a class, every input data value, log message, and error code, amongst other data points, need to be tested.[28] Similar to TDD, non-software teams develop quality control (QC) checks (usually manual tests rather than automated tests) for each aspect of the work prior to commencing. These QC checks are then used to inform the design and validate the associated outcomes. The six steps of the TDD sequence are applied with minor semantic changes:

  1. "Add a check" replaces "Add a test"
  2. "Run all checks" replaces "Run all tests"
  3. "Do the work" replaces "Write some code"
  4. "Run all checks" replaces "Run tests"
  5. "Clean up the work" replaces "Refactor code"
  6. "Repeat"

TDD and ATDD

Test-driven development is related to, but different from acceptance test–driven development (ATDD).[29] TDD is primarily a developer's tool to help create well-written unit of code (function, class, or module) that correctly performs a set of operations. ATDD is a communication tool between the customer, developer, and tester to ensure that the requirements are well-defined. TDD requires test automation. ATDD does not, although automation helps with regression testing. Tests used in TDD can often be derived from ATDD tests, since the code units implement some portion of a requirement. ATDD tests should be readable by the customer. TDD tests do not need to be.

TDD and BDD

BDD (behavior-driven development) combines practices from TDD and from ATDD.[30] It includes the practice of writing tests first, but focuses on tests which describe behavior, rather than tests which test a unit of implementation. Tools such as JBehave, Cucumber, Mspec and Specflow provide syntaxes which allow product owners, developers and test engineers to define together the behaviors which can then be translated into automated tests.

Code visibility

Test suite code clearly has to be able to access the code it is testing. On the other hand, normal design criteria such as information hiding, encapsulation and the separation of concerns should not be compromised. Therefore, unit test code for TDD is usually written within the same project or module as the code being tested.

In object oriented design this still does not provide access to private data and methods. Therefore, extra work may be necessary for unit tests. In Java and other languages, a developer can use reflection to access private fields and methods.[31] Alternatively, an inner class can be used to hold the unit tests so they have visibility of the enclosing class's members and attributes. In the .NET Framework and some other programming languages, partial classes may be used to expose private methods and data for the tests to access.

It is important that such testing hacks do not remain in the production code. In C and other languages, compiler directives such as #if DEBUG ... #endif can be placed around such additional classes and indeed all other test-related code to prevent them being compiled into the released code. This means the released code is not exactly the same as what was unit tested. The regular running of fewer but more comprehensive, end-to-end, integration tests on the final release build can ensure (among other things) that no production code exists that subtly relies on aspects of the test harness.

There is some debate among practitioners of TDD, documented in their blogs and other writings, as to whether it is wise to test private methods and data anyway. Some argue that private members are a mere implementation detail that may change, and should be allowed to do so without breaking numbers of tests. Thus it should be sufficient to test any class through its public interface or through its subclass interface, which some languages call the "protected" interface.[32] Others say that crucial aspects of functionality may be implemented in private methods and testing them directly offers advantage of smaller and more direct unit tests.[33][34]

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Test suite

Test suite

In software development, a test suite, less commonly known as a validation suite, is a collection of test cases that are intended to be used to test a software program to show that it has some specified set of behaviors. A test suite often contains detailed instructions or goals for each collection of test cases and information on the system configuration to be used during testing. A group of test cases may also contain prerequisite states or steps, and descriptions of the following tests.

Information hiding

Information hiding

In computer science, information hiding is the principle of segregation of the design decisions in a computer program that are most likely to change, thus protecting other parts of the program from extensive modification if the design decision is changed. The protection involves providing a stable interface which protects the remainder of the program from the implementation. Written in another way, information hiding is the ability to prevent certain aspects of a class or software component from being accessible to its clients, using either programming language features or an explicit exporting policy.

Separation of concerns

Separation of concerns

In computer science, separation of concerns is a design principle for separating a computer program into distinct sections. Each section addresses a separate concern, a set of information that affects the code of a computer program. A concern can be as general as "the details of the hardware for an application", or as specific as "the name of which class to instantiate". A program that embodies SoC well is called a modular program. Modularity, and hence separation of concerns, is achieved by encapsulating information inside a section of code that has a well-defined interface. Encapsulation is a means of information hiding. Layered designs in information systems are another embodiment of separation of concerns.

Java (programming language)

Java (programming language)

Java is a high-level, class-based, object-oriented programming language that is designed to have as few implementation dependencies as possible. It is a general-purpose programming language intended to let programmers write once, run anywhere (WORA), meaning that compiled Java code can run on all platforms that support Java without the need to recompile. Java applications are typically compiled to bytecode that can run on any Java virtual machine (JVM) regardless of the underlying computer architecture. The syntax of Java is similar to C and C++, but has fewer low-level facilities than either of them. The Java runtime provides dynamic capabilities that are typically not available in traditional compiled languages. As of 2019, Java was one of the most popular programming languages in use according to GitHub, particularly for client–server web applications, with a reported 9 million developers.

Inner class

Inner class

In object-oriented programming (OOP), an inner class or nested class is a class declared entirely within the body of another class or interface. It is distinguished from a subclass.

.NET Framework

.NET Framework

The .NET Framework is a proprietary software framework developed by Microsoft that runs primarily on Microsoft Windows. It was the predominant implementation of the Common Language Infrastructure (CLI) until being superseded by the cross-platform .NET project. It includes a large class library called Framework Class Library (FCL) and provides language interoperability across several programming languages. Programs written for .NET Framework execute in a software environment named the Common Language Runtime (CLR). The CLR is an application virtual machine that provides services such as security, memory management, and exception handling. As such, computer code written using .NET Framework is called "managed code". FCL and CLR together constitute the .NET Framework.

C (programming language)

C (programming language)

C is a general-purpose computer programming language. It was created in the 1970s by Dennis Ritchie, and remains very widely used and influential. By design, C's features cleanly reflect the capabilities of the targeted CPUs. It has found lasting use in operating systems, device drivers, protocol stacks, though decreasingly for application software. C is commonly used on computer architectures that range from the largest supercomputers to the smallest microcontrollers and embedded systems.

Directive (programming)

Directive (programming)

In computer programming, a directive or pragma is a language construct that specifies how a compiler should process its input. Directives are not part of the grammar of a programming language, and may vary from compiler to compiler. They can be processed by a preprocessor to specify compiler behavior, or function as a form of in-band parameterization.

Software for TDD

There are many testing frameworks and tools that are useful in TDD.

xUnit frameworks

Developers may use computer-assisted testing frameworks, commonly collectively named xUnit (which are derived from SUnit, created in 1998), to create and automatically run the test cases. xUnit frameworks provide assertion-style test validation capabilities and result reporting. These capabilities are critical for automation as they move the burden of execution validation from an independent post-processing activity to one that is included in the test execution. The execution framework provided by these test frameworks allows for the automatic execution of all system test cases or various subsets along with other features.[35]

TAP results

Testing frameworks may accept unit test output in the language-agnostic Test Anything Protocol created in 1987.

Fakes, mocks and integration tests

Unit tests are so named because they each test one unit of code. A complex module may have a thousand unit tests and a simple module may have only ten. The unit tests used for TDD should never cross process boundaries in a program, let alone network connections. Doing so introduces delays that make tests run slowly and discourage developers from running the whole suite. Introducing dependencies on external modules or data also turns unit tests into integration tests. If one module misbehaves in a chain of interrelated modules, it is not so immediately clear where to look for the cause of the failure.

When code under development relies on a database, a web service, or any other external process or service, enforcing a unit-testable separation is also an opportunity and a driving force to design more modular, more testable and more reusable code.[36] Two steps are necessary:

  1. Whenever external access is needed in the final design, an interface should be defined that describes the access available. See the dependency inversion principle for a discussion of the benefits of doing this regardless of TDD.
  2. The interface should be implemented in two ways, one of which really accesses the external process, and the other of which is a fake or mock. Fake objects need do little more than add a message such as "Person object saved" to a trace log, against which a test assertion can be run to verify correct behaviour. Mock objects differ in that they themselves contain test assertions that can make the test fail, for example, if the person's name and other data are not as expected.

Fake and mock object methods that return data, ostensibly from a data store or user, can help the test process by always returning the same, realistic data that tests can rely upon. They can also be set into predefined fault modes so that error-handling routines can be developed and reliably tested. In a fault mode, a method may return an invalid, incomplete or null response, or may throw an exception. Fake services other than data stores may also be useful in TDD: A fake encryption service may not, in fact, encrypt the data passed; a fake random number service may always return 1. Fake or mock implementations are examples of dependency injection.

A test double is a test-specific capability that substitutes for a system capability, typically a class or function, that the UUT depends on. There are two times at which test doubles can be introduced into a system: link and execution. Link time substitution is when the test double is compiled into the load module, which is executed to validate testing. This approach is typically used when running in an environment other than the target environment that requires doubles for the hardware level code for compilation. The alternative to linker substitution is run-time substitution in which the real functionality is replaced during the execution of a test case. This substitution is typically done through the reassignment of known function pointers or object replacement.

Test doubles are of a number of different types and varying complexities:

  • Dummy – A dummy is the simplest form of a test double. It facilitates linker time substitution by providing a default return value where required.
  • Stub – A stub adds simplistic logic to a dummy, providing different outputs.
  • Spy – A spy captures and makes available parameter and state information, publishing accessors to test code for private information allowing for more advanced state validation.
  • Mock – A mock is specified by an individual test case to validate test-specific behavior, checking parameter values and call sequencing.
  • Simulator – A simulator is a comprehensive component providing a higher-fidelity approximation of the target capability (the thing being doubled). A simulator typically requires significant additional development effort.[6]

A corollary of such dependency injection is that the actual database or other external-access code is never tested by the TDD process itself. To avoid errors that may arise from this, other tests are needed that instantiate the test-driven code with the "real" implementations of the interfaces discussed above. These are integration tests and are quite separate from the TDD unit tests. There are fewer of them, and they must be run less often than the unit tests. They can nonetheless be implemented using the same testing framework.

Integration tests that alter any persistent store or database should always be designed carefully with consideration of the initial and final state of the files or database, even if any test fails. This is often achieved using some combination of the following techniques:

  • The TearDown method, which is integral to many test frameworks.
  • try...catch...finally exception handling structures where available.
  • Database transactions where a transaction atomically includes perhaps a write, a read and a matching delete operation.
  • Taking a "snapshot" of the database before running any tests and rolling back to the snapshot after each test run. This may be automated using a framework such as Ant or NAnt or a continuous integration system such as CruiseControl.
  • Initialising the database to a clean state before tests, rather than cleaning up after them. This may be relevant where cleaning up may make it difficult to diagnose test failures by deleting the final state of the database before detailed diagnosis can be performed.

Discover more about Fakes, mocks and integration tests related topics

Dependency inversion principle

Dependency inversion principle

In object-oriented design, the dependency inversion principle is a specific methodology for loosely coupling software modules. When following this principle, the conventional dependency relationships established from high-level, policy-setting modules to low-level, dependency modules are reversed, thus rendering high-level modules independent of the low-level module implementation details. The principle states:

Mock object

Mock object

In object-oriented programming, mock objects are simulated objects that mimic the behaviour of real objects in controlled ways, most often as part of a software testing initiative. A programmer typically creates a mock object to test the behaviour of some other object, in much the same way that a car designer uses a crash test dummy to simulate the dynamic behaviour of a human in vehicle impacts. The technique is also applicable in generic programming.

Tracing (software)

Tracing (software)

In software engineering, tracing involves a specialized use of logging to record information about a program's execution. This information is typically used by programmers for debugging purposes, and additionally, depending on the type and detail of information contained in a trace log, by experienced system administrators or technical-support personnel and by software monitoring tools to diagnose common problems with software. Tracing is a cross-cutting concern.

Null character

Null character

The null character is a control character with the value zero. It is present in many character sets, including those defined by the Baudot and ITA2 codes, ISO/IEC 646, the C0 control code, the Universal Coded Character Set, and EBCDIC. It is available in nearly all mainstream programming languages. It is often abbreviated as NUL. In 8-bit codes, it is known as a null byte.

Exception handling

Exception handling

In computing and computer programming, exception handling is the process of responding to the occurrence of exceptions – anomalous or exceptional conditions requiring special processing – during the execution of a program. In general, an exception breaks the normal flow of execution and executes a pre-registered exception handler; the details of how this is done depend on whether it is a hardware or software exception and how the software exception is implemented. Exception handling, if provided, is facilitated by specialized programming language constructs, hardware mechanisms like interrupts, or operating system (OS) inter-process communication (IPC) facilities like signals. Some exceptions, especially hardware ones, may be handled so gracefully that execution can resume where it was interrupted.

Dependency injection

Dependency injection

In software engineering, dependency injection is a design pattern in which an object or function receives other objects or functions that it depends on. A form of inversion of control, dependency injection aims to separate the concerns of constructing objects and using them, leading to loosely coupled programs. The pattern ensures that an object or function which wants to use a given service should not have to know how to construct those services. Instead, the receiving 'client' is provided with its dependencies by external code, which it is not aware of. Dependency injection helps by making implicit dependencies explicit and helps solve the following problems:How can a class be independent from the creation of the objects it depends on? How can an application, and the objects it uses support different configurations? How can the behavior of a piece of code be changed without editing it directly?

Method stub

Method stub

A method stub or simply stub in software development is a piece of code used to stand in for some other programming functionality. A stub may simulate the behavior of existing code or be a temporary substitute for yet-to-be-developed code. Stubs are therefore most useful in porting, distributed computing as well as general software development and testing.

Integration testing

Integration testing

Integration testing is the phase in software testing in which individual software modules are combined and tested as a group. Integration testing is conducted to evaluate the compliance of a system or component with specified functional requirements. It occurs after unit testing and before system testing. Integration testing takes as its input modules that have been unit tested, groups them in larger aggregates, applies tests defined in an integration test plan to those aggregates, and delivers as its output the integrated system ready for system testing.

Atomicity (database systems)

Atomicity (database systems)

In database systems, atomicity is one of the ACID transaction properties. An atomic transaction is an indivisible and irreducible series of database operations such that either all occurs, or nothing occurs. A guarantee of atomicity prevents updates to the database occurring only partially, which can cause greater problems than rejecting the whole series outright. As a consequence, the transaction cannot be observed to be in progress by another database client. At one moment in time, it has not yet happened, and at the next it has already occurred in whole.

Apache Ant

Apache Ant

Apache Ant is a software tool for automating software build processes which originated from the Apache Tomcat project in early 2000 as a replacement for the Make build tool of Unix. It is similar to Make, but is implemented using the Java language and requires the Java platform. Unlike Make, which uses the Makefile format, Ant uses XML to describe the code build process and its dependencies.

NAnt

NAnt

NAnt is a free and open source software tool for automating software build processes. It is similar to Apache Ant, but targeted at the .NET environment rather than Java. The name NAnt comes from the fact that the tool is Not Ant.

Continuous integration

Continuous integration

In software engineering, continuous integration (CI) is the practice of merging all developers' working copies to a shared mainline several times a day. Grady Booch first proposed the term CI in his 1991 method, although he did not advocate integrating several times a day. Extreme programming (XP) adopted the concept of CI and did advocate integrating more than once per day – perhaps as many as tens of times per day.

TDD for complex systems

Exercising TDD on large, challenging systems requires a modular architecture, well-defined components with published interfaces, and disciplined system layering with maximization of platform independence. These proven practices yield increased testability and facilitate the application of build and test automation.[6]

Designing for testability

Complex systems require an architecture that meets a range of requirements. A key subset of these requirements includes support for the complete and effective testing of the system. Effective modular design yields components that share traits essential for effective TDD.

  • High Cohesion ensures each unit provides a set of related capabilities and makes the tests of those capabilities easier to maintain.
  • Low Coupling allows each unit to be effectively tested in isolation.
  • Published Interfaces restrict Component access and serve as contact points for tests, facilitating test creation and ensuring the highest fidelity between test and production unit configuration.

A key technique for building effective modular architecture is Scenario Modeling where a set of sequence charts is constructed, each one focusing on a single system-level execution scenario. The Scenario Model provides an excellent vehicle for creating the strategy of interactions between components in response to a specific stimulus. Each of these Scenario Models serves as a rich set of requirements for the services or functions that a component must provide, and it also dictates the order in which these components and services interact together. Scenario modeling can greatly facilitate the construction of TDD tests for a complex system.[6]

Managing tests for large teams

In a larger system, the impact of poor component quality is magnified by the complexity of interactions. This magnification makes the benefits of TDD accrue even faster in the context of larger projects. However, the complexity of the total population of tests can become a problem in itself, eroding potential gains. It sounds simple, but a key initial step is to recognize that test code is also important software and should be produced and maintained with the same rigor as the production code.

Creating and managing the architecture of test software within a complex system is just as important as the core product architecture. Test drivers interact with the UUT, test doubles and the unit test framework.[6]

Conference

First TDD Conference was held during July 2021.[37] Conferences were recorded on YouTube[38]

Discover more about TDD for complex systems related topics

Cohesion (computer science)

Cohesion (computer science)

In computer programming, cohesion refers to the degree to which the elements inside a module belong together. In one sense, it is a measure of the strength of relationship between the methods and data of a class and some unifying purpose or concept served by that class. In another sense, it is a measure of the strength of relationship between the class's methods and data themselves.

Coupling (computer programming)

Coupling (computer programming)

In software engineering, coupling is the degree of interdependence between software modules; a measure of how closely connected two routines or modules are; the strength of the relationships between modules.

Software architecture

Software architecture

Software architecture refers to the fundamental structures of a software system and the discipline of creating such structures and systems. Each structure comprises software elements, relations among them, and properties of both elements and relations.

Test double

Test double

In computer programming and computer science, programmers employ a technique called automated unit testing to reduce the likelihood of bugs occurring in the software. Frequently, the final release software consists of a complex set of objects or procedures interacting together to create the final result. In automated unit testing, it may be necessary to use objects or procedures that look and behave like their release-intended counterparts, but are actually simplified versions that reduce the complexity and facilitate testing. A test double is a generic (meta) term used for these objects or procedures.

YouTube

YouTube

YouTube is an American online video sharing and social media platform headquartered in San Bruno, California. It was launched on February 14, 2005, by Steve Chen, Chad Hurley, and Jawed Karim. It is owned by Google, and is the second most visited website, after Google Search. YouTube has more than 2.5 billion monthly users who collectively watch more than one billion hours of videos each day. As of May 2019, videos were being uploaded at a rate of more than 500 hours of content per minute.

Source: "Test-driven development", Wikipedia, Wikimedia Foundation, (2022, November 25th), https://en.wikipedia.org/wiki/Test-driven_development.

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See also
References
  1. ^ Kent Beck (May 11, 2012). "Why does Kent Beck refer to the "rediscovery" of test-driven development?". Retrieved December 1, 2014.
  2. ^ a b c Beck, Kent (2002-11-08). Test-Driven Development by Example. Vaseem: Addison Wesley. ISBN 978-0-321-14653-3.
  3. ^ Lee Copeland (December 2001). "Extreme Programming". Computerworld. Archived from the original on June 5, 2011. Retrieved January 11, 2011.
  4. ^ a b Newkirk, JW and Vorontsov, AA. Test-Driven Development in Microsoft .NET, Microsoft Press, 2004.
  5. ^ Feathers, M. Working Effectively with Legacy Code, Prentice Hall, 2004
  6. ^ a b c d e f g "Effective TDD for Complex Embedded Systems Whitepaper" (PDF). Pathfinder Solutions. Archived from the original (PDF) on 2016-03-16.
  7. ^ "Agile Test Driven Development". Agile Sherpa. 2010-08-03. Archived from the original on 2012-07-23. Retrieved 2012-08-14.
  8. ^ Koskela, L. "Test Driven: TDD and Acceptance TDD for Java Developers", Manning Publications, 2007
  9. ^ a b Test-Driven Development (TDD) for Complex Systems Introduction on YouTube by Pathfinder Solutions
  10. ^ Erdogmus, Hakan; Morisio, Torchiano. "On the Effectiveness of Test-first Approach to Programming". Proceedings of the IEEE Transactions on Software Engineering, 31(1). January 2005. (NRC 47445). Archived from the original on 2014-12-22. Retrieved 2008-01-14. We found that test-first students on average wrote more tests and, in turn, students who wrote more tests tended to be more productive.
  11. ^ Proffitt, Jacob. "TDD Proven Effective! Or is it?". Archived from the original on 2008-02-06. Retrieved 2008-02-21. So TDD's relationship to quality is problematic at best. Its relationship to productivity is more interesting. I hope there's a follow-up study because the productivity numbers simply don't add up very well to me. There is an undeniable correlation between productivity and the number of tests, but that correlation is actually stronger in the non-TDD group (which had a single outlier compared to roughly half of the TDD group being outside the 95% band).
  12. ^ Llopis, Noel (20 February 2005). "Stepping Through the Looking Glass: Test-Driven Game Development (Part 1)". Games from Within. Retrieved 2007-11-01. Comparing [TDD] to the non-test-driven development approach, you're replacing all the mental checking and debugger stepping with code that verifies that your program does exactly what you intended it to do.
  13. ^ Mayr, Herwig (2005). Projekt Engineering Ingenieurmässige Softwareentwicklung in Projektgruppen (2., neu bearb. Aufl. ed.). München: Fachbuchverl. Leipzig im Carl-Hanser-Verl. p. 239. ISBN 978-3446400702.
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  16. ^ The impact of Test-First programming on branch coverage and mutation score indicator of unit tests: An experiment. by L. Madeyski Information & Software Technology 52(2): 169-184 (2010)
  17. ^ On the Effects of Pair Programming on Thoroughness and Fault-Finding Effectiveness of Unit Tests by L. Madeyski PROFES 2007: 207-221
  18. ^ Impact of pair programming on thoroughness and fault detection effectiveness of unit test suites. by L. Madeyski Software Process: Improvement and Practice 13(3): 281-295 (2008)
  19. ^ M. Pančur and M. Ciglarič, "Impact of test-driven development on productivity, code and tests: A controlled experiment", Information and Software Technology, 2011, vol. 53, no. 6, pp. 557–573, DOI: 10.1016/j.infsof.2011.02.002
  20. ^ D. Fucci, H. Erdogmus, B. Turhan, M. Oivo, and N. Juristo, "A dissection of the test-driven development process: does it really matter to test-first or to test-last?", IEEE Transactions on Software Engineering, 2017, vol. 43, no. 7, pp. 597–614, DOI: 10.1109/TSE.2016.2616877
  21. ^ A. Tosun, O. Dieste Tubio, D. Fucci, S. Vegas, B. Turhan, H. Erdogmus, A. Santos, M. Oivo, K. Toro, J. Jarvinen, and N. Juristo, "An industry experiment on the effects of test-driven development on external quality and productivity", Empirical Software Engineering, 2016, vol. 22, pp. 1–43, DOI: 10.1007/s10664-016-9490-0
  22. ^ B. Papis, K. Grochowski, K. Subzda and K. Sijko, "Experimental evaluation of test-driven development with interns working on a real industrial project", IEEE Transactions on Software Engineering, 2020, DOI: 10.1109/TSE.2020.3027522
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