Editing Test-driven development (section)

== Advantages and Disadvantages of Test Driven Development ==

=== Advantages ===

Test Driven Development (TDD) is a software development approach where tests are written before the actual code. It offers several advantages:

# '''Comprehensive Test Coverage''': TDD ensures that all new code is covered by at least one test, leading to more robust software.
# '''Enhanced Confidence in Code''': Developers gain greater confidence in the code's reliability and functionality.
# '''Enhanced Confidence in Tests''': As the tests are known to be failing without the proper implementation, we know that the tests actually tests the implementation correctly.
# '''Well-Documented Code''': The process naturally results in well-documented code, as each test clarifies the purpose of the code it tests.
# '''Requirement Clarity''': TDD encourages a clear understanding of requirements before coding begins.
# '''Facilitates Continuous Integration''': It integrates well with continuous integration processes, allowing for frequent code updates and testing.
# '''Boosts Productivity''': Many developers find that TDD increases their productivity.
# '''Reinforces Code Mental Model''': TDD helps in building a strong mental model of the code's structure and behavior.
# '''Emphasis on Design and Functionality''': It encourages a focus on the design, interface, and overall functionality of the program.
# '''Reduces Need for Debugging''': By catching issues early in the development process, TDD reduces the need for extensive debugging later.
# '''System Stability''': Applications developed with TDD tend to be more stable and less prone to bugs.<ref>[https://lasoft.org/blog/test-driven-development-tdd/ Advantages and Disadvantages of Test Driven Development - LASOFT]</ref>

=== Disadvantages ===

However, TDD is not without its drawbacks:

# '''Increased Code Volume''': Implementing TDD can result in a larger codebase as tests add to the total amount of code written.
# '''False Security from Tests''': A large number of passing tests can sometimes give a misleading sense of security regarding the code's robustness.<ref>{{Cite journal |last1=Parsa |first1=Saeed |last2=Zakeri-Nasrabadi |first2=Morteza |last3=Turhan |first3=Burak |date=2025-01-01 |title=Testability-driven development: An improvement to the TDD efficiency |url=https://www.sciencedirect.com/science/article/pii/S0920548924000461 |journal=Computer Standards & Interfaces |volume=91 |pages=103877 |doi=10.1016/j.csi.2024.103877 |issn=0920-5489}}</ref>
# '''Maintenance Overheads''': Maintaining a large suite of tests can add overhead to the development process.
# '''Time-Consuming Test Processes''': Writing and maintaining tests can be time-consuming.
# '''Testing Environment Set-Up''': TDD requires setting up and maintaining a suitable testing environment.
# '''Learning Curve''': It takes time and effort to become proficient in TDD practices.
# '''Overcomplication''': An overemphasis on TDD can lead to code that is more complex than necessary.
# '''Neglect of Overall Design''': Focusing too narrowly on passing tests can sometimes lead to neglect of the bigger picture in software design.
# '''Increased Costs''': The additional time and resources required for TDD can result in higher development costs.

=== 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.<ref>{{cite web
 | url = http://nparc.cisti-icist.nrc-cnrc.gc.ca/npsi/ctrl?action=shwart&index=an&req=5763742&lang=en
 | title = On the Effectiveness of Test-first Approach to Programming
 | access-date = 2008-01-14
 | last = Erdogmus
 | first = Hakan
 | author2 = Morisio, Torchiano
 | publisher = Proceedings of the IEEE Transactions on Software Engineering, 31(1). January 2005. (NRC 47445)
 | quote = We found that test-first students on average wrote more tests and, in turn, students who wrote more tests tended to be more productive.
 | archive-url = https://web.archive.org/web/20141222180731/http://nparc.cisti-icist.nrc-cnrc.gc.ca/npsi/ctrl?action=shwart&index=an&req=5763742&lang=en
 | archive-date = 2014-12-22
 | url-status = dead
 }}</ref> Hypotheses relating to code quality and a more direct correlation between TDD and productivity were inconclusive.<ref>{{cite web
 | url = http://theruntime.com/blogs/jacob/archive/2008/01/22/tdd-proven-effective-or-is-it.aspx
 | title = TDD Proven Effective! Or is it?
 | access-date = 2008-02-21
 | last = Proffitt
 | first = Jacob
 | quote = 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).
 | archive-url = https://web.archive.org/web/20080206103552/http://theruntime.com/blogs/jacob/archive/2008/01/22/tdd-proven-effective-or-is-it.aspx
 | archive-date = 2008-02-06
 | url-status = dead
 }}</ref>

Programmers using pure TDD on new ("[[Greenfield project|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.<ref>{{cite web
 | url = http://gamesfromwithin.com/stepping-through-the-looking-glass-test-driven-game-development-part-1
 | title = Stepping Through the Looking Glass: Test-Driven Game Development (Part 1)
 | access-date = 2007-11-01
 | last = Llopis
 | first = Noel
 | date = 20 February 2005
 | publisher = Games from Within
 | quote = 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.
}}</ref>

Test-driven development offers more than just simple validation of correctness, but can also drive the design of a program.<ref>{{cite book|last1=Mayr|first1=Herwig|title=Projekt Engineering Ingenieurmässige Softwareentwicklung in Projektgruppen|date=2005|publisher=Fachbuchverl. Leipzig im Carl-Hanser-Verl.|location=München|isbn=978-3446400702|page=239|edition=2., neu bearb. Aufl.}}</ref> 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.<ref>{{cite web
 | url = https://pdfs.semanticscholar.org/65d9/24ef1162b2f3c24bd15d627302887991b298.pdf
 | archive-url = https://web.archive.org/web/20171108092303/https://pdfs.semanticscholar.org/65d9/24ef1162b2f3c24bd15d627302887991b298.pdf
 | url-status = dead
 | archive-date = 2017-11-08
 | title = About the Return on Investment of Test-Driven Development
 | access-date = 2012-06-14
 | last = Müller
 | first = Matthias M.
 |author2=Padberg, Frank
  | publisher = Universität Karlsruhe, Germany
 | page = 6
| s2cid = 13905442
 }}</ref> 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 (computer programming)|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 <code>else</code> branch to an existing <code>if</code> 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<ref name="Madeyski">Madeyski, L. "Test-Driven Development - An Empirical Evaluation of Agile Practice", Springer, 2010, {{ISBN|978-3-642-04287-4}}, pp. 1-245. DOI: 978-3-642-04288-1</ref> 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.<ref name="Madeyski" /> Madeyski also measured the effect of the TDD practice on unit tests using branch coverage (BC) and mutation score indicator (MSI),<ref>[http://madeyski.e-informatyka.pl/download/Madeyski10c.pdf 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)''</ref><ref>[http://madeyski.e-informatyka.pl/download/Madeyski07.pdf On the Effects of Pair Programming on Thoroughness and Fault-Finding Effectiveness of Unit Tests] by L. Madeyski ''PROFES 2007: 207-221''</ref><ref>[http://madeyski.e-informatyka.pl/download/Madeyski08.pdf 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)''</ref> 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.<ref name="Madeyski" /> These findings have been subsequently confirmed by further, smaller experimental evaluations of TDD.<ref name="Pančur">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</ref><ref name="Fucci">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</ref><ref name="Tosun">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</ref><ref name="Papis">B. Papis, K. Grochowski, K. Subzda and K. Sijko, [https://ieeexplore.ieee.org/document/9207972 "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</ref>

=== Psychological benefits to programmer ===

# '''Increased Confidence''': TDD allows programmers to make changes or add new features with confidence. Knowing that the code is constantly tested reduces the fear of breaking existing functionality. This safety net can encourage more innovative and creative approaches to problem-solving.
# '''Reduced Fear of Change, Reduced Stress''': In traditional development, changing existing code can be daunting due to the risk of introducing bugs. TDD, with its comprehensive test suite, reduces this fear, as tests will immediately reveal any problems caused by changes. Knowing that the codebase has a safety net of tests can reduce stress and anxiety associated with programming. Developers might feel more relaxed and open to experimenting and refactoring.
# '''Improved Focus''': Writing tests first helps programmers concentrate on requirements and design before writing the code. This focus can lead to clearer, more purposeful coding, as the developer is always aware of the goal they are trying to achieve.
# '''Sense of Achievement and Job Satisfaction''': Passing tests can provide a quick, regular sense of accomplishment, boosting morale. This can be particularly motivating in long-term projects where the end goal might seem distant. The combination of all these factors can lead to increased job satisfaction. When developers feel confident, focused, and part of a collaborative team, their overall job satisfaction can significantly improve.

=== Limitations ===
{{more citations needed section|date=August 2013}}
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.<ref>
{{cite web
 | url=http://dalkescientific.com/writings/diary/archive/2009/12/29/problems_with_tdd.html
 | title=Problems with TDD
 | publisher=Dalkescientific.com
 | date=2009-12-29
 | access-date=2014-03-25}}</ref> Examples of these are [[user interface]]s, programs that work with [[database]]s, and some that depend on specific [[Computer network|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 [[Mock object|mocks]] to represent the outside world.<ref>
{{cite web
 | last=Hunter
 | first=Andrew
 | url=https://www.simple-talk.com/dotnet/.net-framework/are-unit-tests-overused/
 | title=Are Unit Tests Overused?
 | work=Simple Talk
 | publisher=Simple-talk.com
 | date=2012-10-19 |access-date=2014-03-25}}</ref>

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.<ref>
{{cite web
 | url=http://people.apache.org/~stevel/slides/testing.pdf
 | title=Testing
 | last=Loughran
 | first=Steve
 | date=November 6, 2006
 | publisher=HP Laboratories
 | access-date=2009-08-12
 }}</ref>

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]].<ref>
{{cite web
 | url=http://xunitpatterns.com/Fragile%20Test.html
 | title=Fragile Tests
}}</ref> 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.