Unit testing

Unit testing, as a principle for testing separately smaller parts of large software systems, dates back to the early days of software engineering. In June 1956 at US Navy's Symposium on Advanced Programming Methods for Digital Computers, H.D. Benington presented the SAGE project. It featured a specification-based approach where the coding phase was followed by "parameter testing" to validate component subprograms against their specification, followed then by an "assembly testing" for parts put together.{{Cite journal |last=Benington |first=Herbert D. |date=1956 |title=Production of large computer programs |journal=Proceedings of the Symposium on Advanced Programming Methods for Digital Computers, Washington, D.C., June 28-29, 1956 |publisher=Office of Naval Research, Department of the Navy |pages=15–28}}{{Cite journal |last=Benington |first=H. D. |date=1987-03-01 |title=Production of large computer programs (reprint of the 1956 paper with an updated foreword) |url=https://dl.acm.org/doi/10.5555/41765.41799 |journal=Proceedings of the 9th International Conference on Software Engineering |series=ICSE '87 |location=Washington, DC, USA |publisher=IEEE Computer Society Press |pages=299–310 |isbn=978-0-89791-216-7 }}

In 1964, a similar approach is described for the software of the Mercury project, where individual units developed by different programmes underwent "unit tests" before being integrated together.{{Cite book |last1=Donegan |first1=James J. |last2=Packard |first2=Calvin |last3=Pashby |first3=Paul |chapter=Experiences with the goddard computing system during manned spaceflight missions |date=1964-01-01 |title=Proceedings of the 1964 19th ACM national conference |chapter-url=https://dl.acm.org/doi/10.1145/800257.808889 |series=ACM '64 |location=New York, NY, USA |publisher=Association for Computing Machinery |pages=12.101–12.108 |doi=10.1145/800257.808889 |isbn=978-1-4503-7918-2}} In 1969, testing methodologies appear more structured, with unit tests, component tests and integration tests collectively validating individual parts written separately and their progressive assembly into larger blocks.{{Cite book |last=Zimmerman |first=Norman A. |chapter=System integration as a programming function |date=1969-08-26 |title=Proceedings of the 1969 24th national conference |chapter-url=https://dl.acm.org/doi/10.1145/800195.805951 |series=ACM '69 |location=New York, NY, USA |publisher=Association for Computing Machinery |pages=459–467 |doi=10.1145/800195.805951 |isbn=978-1-4503-7493-4}} Some public standards adopted in the late 1960s, such as MIL-STD-483{{Cite book |title=MIL-STD-483 Military standard: configuration management practices for systems, equipment, munitions, and computer programs |date=1970-12-31 |publisher=United states, Department of Defense |year=1970 |pages=Section 3.4.7.2 |quote=The contractor shall then code and test software Units, and enter the source and object code, and associated listings of each successfully tested Unit into the Developmental Configuration}} and MIL-STD-490, contributed further to a wide acceptance of unit testing in large projects.

Unit testing was in those times interactive or automated,{{Cite journal |last=Tighe |first=Michael F. |date=1978-01-01 |title=The value of a proper software quality assurance methodology |url=https://dl.acm.org/doi/10.1145/1007775.811118 |journal=ACM SIGMETRICS Performance Evaluation Review |volume=7 |issue=3–4 |pages=165–172 |doi=10.1145/1007775.811118 |issn=0163-5999}} using either coded tests or capture and replay testing tools. In 1989, Kent Beck described a testing framework for Smalltalk (later called SUnit) in "[https://web.archive.org/web/20150315073817/http://www.xprogramming.com/testfram.htm Simple Smalltalk Testing: With Patterns]". In 1997, Kent Beck and Erich Gamma developed and released JUnit, a unit test framework that became popular with Java developers.{{Cite book |last=Gulati |first=Shekhar |url= |title=Java Unit Testing with JUnit 5 : Test Driven Development with JUnit 5 |date=2017 |publisher=Apress |others=Rahul Sharma |isbn=978-1-4842-3015-2 |location=Berkeley, CA |pages=8 |oclc=1012347252}} Google embraced automated testing around 2005–2006.{{Cite book |last=Winters |first=Titus |title=Software engineering at Google : lessons learned from programming over time |date=2020 |publisher=O'Reilly |others=Tom Manshreck, Hyrum Wright |isbn=978-1-4920-8274-3 |edition=1st |location=Sebastopol, CA |oclc=1144086840}}

A unit is defined as a single behaviour exhibited by the system under test (SUT), usually corresponding to a requirement{{Definition needed|date=January 2025}}. While a unit may correspond to a single function or module (in procedural programming) or a single method or class (in object-oriented programming), functions/methods and modules/classes do not necessarily correspond to units. From the system requirements perspective only the perimeter of the system is relevant, thus only entry points to externally visible system behaviours define units.{{Clarify|date=January 2025}}{{cite book |last=Beck

|first=Kent

|author-link=Kent Beck

|date=2002

|title= Test-Driven Development by Example

|publisher=Addison-Wesley

|isbn=978-0321146533}}

Unit tests can be performed manually or via automated test execution. Automated tests include benefits such as: running tests often, running tests without staffing cost, and consistent and repeatable testing.

Testing is often performed by the programmer who writes and modifies the code under test.

Unit testing may be viewed as part of the process of writing code.

{{More citations needed section|date=September 2019}}

Unit testing, {{aka}} component or module testing, is a form of software testing by which isolated source code is tested to validate expected behavior.

Unit testing describes tests that are run at the unit-level to contrast testing at the integration or system level.

{{Excerpt|Test case|paragraphs=1|only=paragraph}}

{{Excerpt|Test double|paragraphs=1|only=paragraph}}

A parameterized test is a test that accepts a set of values that can be used to enable the test to run with multiple, different input values. A testing framework that supports parametrized tests supports a way to encode parameter sets and to run the test with each set.

Use of parametrized tests can reduce test code duplication.

Parameterized tests are supported by TestNG, JUnit,{{sfn|Gulati|Sharma|2017|loc=Chapter §7 JUnit 5 Extension Model - Parameterized Test|pp=133-137}} XUnit and NUnit, as well as in various JavaScript test frameworks.{{cn|date=November 2023}}

Parameters for the unit tests may be coded manually or in some cases are automatically generated by the test framework. In recent years support was added for writing more powerful (unit) tests, leveraging the concept of theories, test cases that execute the same steps, but using test data generated at runtime, unlike regular parameterized tests that use the same execution steps with input sets that are pre-defined.{{cn|date=November 2023}}

{{Main|Agile software development}}

Sometimes, in the agile software development, unit testing is done per user story and comes in the later half of the sprint after requirements gathering and development are complete. Typically, the developers or other members from the development team, such as consultants, will write step-by-step 'test scripts' for the developers to execute in the tool. Test scripts are generally written to prove the effective and technical operation of specific developed features in the tool, as opposed to full fledged business processes that would be interfaced by the end user, which is typically done during user acceptance testing. If the test-script can be fully executed from start to finish without incident, the unit test is considered to have "passed", otherwise errors are noted and the user story is moved back to development in an 'in-progress' state. User stories that successfully pass unit tests are moved on to the final steps of the sprint - Code review, peer review, and then lastly a 'show-back' session demonstrating the developed tool to stakeholders.

{{Main|Test-driven development}}

In test-driven development (TDD), unit tests are written while the production code is written. Starting with working code, the developer adds test code for a required behavior, then adds just enough code to make the test pass, then refactors the code (including test code) as makes sense and then repeats by adding another test.

Unit testing is intended to ensure that the units meet their design and behave as intended.{{cite book |last1=Hamill |first1=Paul |title=Unit Test Frameworks: Tools for High-Quality Software Development |date=2004 |publisher=O'Reilly Media, Inc.|isbn=9780596552817 |url=https://books.google.com/books?id=2ksvdhhnWQsC}}

By writing tests first for the smallest testable units, then the compound behaviors between those, one can build up comprehensive tests for complex applications.

One goal of unit testing is to isolate each part of the program and show that the individual parts are correct. A unit test provides a strict, written contract that the piece of code must satisfy.

Unit testing finds problems early in the development cycle. This includes both bugs in the programmer's implementation and flaws or missing parts of the specification for the unit. The process of writing a thorough set of tests forces the author to think through inputs, outputs, and error conditions, and thus more crisply define the unit's desired behavior.{{cn|date=November 2023}}

The cost of finding a bug before coding begins or when the code is first written is considerably lower than the cost of detecting, identifying, and correcting the bug later. Bugs in released code may also cause costly problems for the end-users of the software.{{cite journal |last1=Boehm |first1=Barry W. |author-link1=Barry Boehm |last2=Papaccio |first2=Philip N. |date=October 1988 |title=Understanding and Controlling Software Costs |url=http://faculty.ksu.edu.sa/ghazy/Cost_MSc/R6.pdf |journal=IEEE Transactions on Software Engineering |volume=14 |issue=10 |pages=1462–1477 |doi=10.1109/32.6191 |access-date=13 May 2016 |archive-date=9 October 2016 |archive-url=https://web.archive.org/web/20161009084506/http://faculty.ksu.edu.sa/ghazy/Cost_MSc/R6.pdf |url-status=dead }}{{cite web|url=https://msdn.microsoft.com/en-us/library/ee330950%28v=vs.110%29.aspx|title=Test Early and Often|publisher=Microsoft}}{{cite web|url=http://www.ni.com/white-paper/8082/en/| title=Prove It Works: Using the Unit Test Framework for Software Testing and Validation| publisher=National Instruments| date=2017-08-21}} Code can be impossible or difficult to unit test if poorly written, thus unit testing can force developers to structure functions and objects in better ways.

Unit testing enables more frequent releases in software development. By testing individual components in isolation, developers can quickly identify and address issues, leading to faster iteration and release cycles.{{cite web |last1=Erik |title=You Still Don't Know How to Do Unit Testing (and Your Secret is Safe with Me) |url=https://stackify.com/unit-testing-basics-best-practices/ |website=Stackify |date=10 March 2023 |access-date=10 March 2023}}

Unit testing allows the programmer to refactor code or upgrade system libraries at a later date, and make sure the module still works correctly (e.g., in regression testing). The procedure is to write test cases for all functions and methods so that whenever a change causes a fault, it can be identified quickly.

Unit tests detect changes which may break a design contract.

Unit testing may reduce uncertainty in the units themselves and can be used in a bottom-up testing style approach. By testing the parts of a program first and then testing the sum of its parts, integration testing becomes much easier.{{Citation needed|date=January 2013}}

Some programmers contend that unit tests provide a form of documentation of the code. Developers wanting to learn what functionality is provided by a unit, and how to use it, can review the unit tests to gain an understanding of it.{{Citation needed|date=September 2019}}

Test cases can embody characteristics that are critical to the success of the unit. These characteristics can indicate appropriate/inappropriate use of a unit as well as negative behaviors that are to be trapped by the unit. A test case documents these critical characteristics, although many software development environments do not rely solely upon code to document the product in development.{{Citation needed|date=September 2019}}

In some processes, the act of writing tests and the code under test, plus associated refactoring, may take the place of formal design. Each unit test can be seen as a design element specifying classes, methods, and observable behavior.{{Citation needed|date=September 2019}}

Testing will not catch every error in the program, because it cannot evaluate every execution path in any but the most trivial programs. This problem is a superset of the halting problem, which is undecidable. The same is true for unit testing. Additionally, unit testing by definition only tests the functionality of the units themselves. Therefore, it will not catch integration errors or broader system-level errors (such as functions performed across multiple units, or non-functional test areas such as performance). Unit testing should be done in conjunction with other software testing activities, as they can only show the presence or absence of particular errors; they cannot prove a complete absence of errors. To guarantee correct behavior for every execution path and every possible input, and ensure the absence of errors, other techniques are required, namely the application of formal methods to prove that a software component has no unexpected behavior.{{Citation needed|date=September 2019}}

An elaborate hierarchy of unit tests does not equal integration testing. Integration with peripheral units should be included in integration tests, but not in unit tests.{{Citation needed|date=October 2010}} Integration testing typically still relies heavily on humans testing manually; high-level or global-scope testing can be difficult to automate, such that manual testing often appears faster and cheaper.{{Citation needed|date=January 2010}}

Software testing is a combinatorial problem. For example, every Boolean decision statement requires at least two tests: one with an outcome of "true" and one with an outcome of "false". As a result, for every line of code written, programmers often need 3 to 5 lines of test code.{{cn|date=November 2023}} This obviously takes time and its investment may not be worth the effort. There are problems that cannot easily be tested at all – for example those that are nondeterministic or involve multiple threads. In addition, code for a unit test is as likely to be buggy as the code it is testing. Fred Brooks in The Mythical Man-Month quotes: "Never go to sea with two chronometers; take one or three."{{Cite book | isbn = 978-0-201-83595-3 | title = The Mythical Man-Month | last = Brooks | first = Frederick J. | author-link = Fred Brooks | year = 1995 | orig-year = 1975 | publisher = Addison-Wesley | page = [https://archive.org/details/mythicalmonth00broo/page/64 64] | title-link = The Mythical Man-Month }} Meaning, if two chronometers contradict, how do you know which one is correct?

Another challenge related to writing the unit tests is the difficulty of setting up realistic and useful tests. It is necessary to create relevant initial conditions so the part of the application being tested behaves like part of the complete system. If these initial conditions are not set correctly, the test will not be exercising the code in a realistic context, which diminishes the value and accuracy of unit test results.{{cn|date=November 2023}}

To obtain the intended benefits from unit testing, rigorous discipline is needed throughout the software development process.

It is essential to keep careful records not only of the tests that have been performed, but also of all changes that have been made to the source code of this or any other unit in the software. Use of a version control system is essential. If a later version of the unit fails a particular test that it had previously passed, the version-control software can provide a list of the source code changes (if any) that have been applied to the unit since that time.{{Citation needed|date=September 2019}}

It is also essential to implement a sustainable process for ensuring that test case failures are reviewed regularly and addressed immediately.{{cite web|last=daVeiga|first=Nada|author-link=Nada daVeiga| title=Change Code Without Fear: Utilize a regression safety net|date=2008-02-06| access-date=2008-02-08|url=http://www.ddj.com/development-tools/206105233}} If such a process is not implemented and ingrained into the team's workflow, the application will evolve out of sync with the unit test suite, increasing false positives and reducing the effectiveness of the test suite.

Unit testing embedded system software presents a unique challenge: Because the software is being developed on a different platform than the one it will eventually run on, you cannot readily run a test program in the actual deployment environment, as is possible with desktop programs.{{cite web|last=Kucharski|first=Marek|author-link=Marek Kucharski| title=Making Unit Testing Practical for Embedded Development|date=2011-11-23| access-date=2020-07-20|url=https://www.electronicdesign.com/technologies/embedded-revolution/article/21794376/making-unit-testing-practical-for-embedded-development}}

Unit tests tend to be easiest when a method has input parameters and some output. It is not as easy to create unit tests when a major function of the method is to interact with something external to the application. For example, a method that will work with a database might require a mock up of database interactions to be created, which probably won't be as comprehensive as the real database interactions.{{cite web| url=http://wiki.c2.com/?UnitTestsAndDatabases | title=Unit Tests And Databases | access-date=2024-01-29}}{{better source needed|date=February 2019}}

Below is an example of a JUnit test suite. It focuses on the {{code|Adder}} class.

class Adder {

public int add(int a, int b) {

return a + b;

}

}

The test suite uses assert statements to verify the expected result of various input values to the {{code|sum}} method.

import static org.junit.Assert.assertEquals;

import org.junit.Test;

public class AdderUnitTest {

@Test

public void sumReturnsZeroForZeroInput() {

Adder adder = new Adder();

assertEquals(0, adder.add(0, 0));

}

@Test

public void sumReturnsSumOfTwoPositiveNumbers() {

Adder adder = new Adder();

assertEquals(3, adder.add(1, 2));

}

@Test

public void sumReturnsSumOfTwoNegativeNumbers() {

Adder adder = new Adder();

assertEquals(-3, adder.add(-1, -2));

}

@Test

public void sumReturnsSumOfLargeNumbers() {

Adder adder = new Adder();

assertEquals(2222, adder.add(1234, 988));

}

}

{{Unreferenced section|date=September 2019}}

Using unit-tests as a design specification has one significant advantage over other design methods: The design document (the unit-tests themselves) can itself be used to verify the implementation. The tests will never pass unless the developer implements a solution according to the design.

Unit testing lacks some of the accessibility of a diagrammatic specification such as a UML diagram, but they may be generated from the unit test using automated tools. Most modern languages have free tools (usually available as extensions to IDEs). Free tools, like those based on the xUnit framework, outsource to another system the graphical rendering of a view for human consumption.

Unit testing is the cornerstone of extreme programming, which relies on an automated unit testing framework. This automated unit testing framework can be either third party, e.g., xUnit, or created within the development group.

Extreme programming uses the creation of unit tests for test-driven development. The developer writes a unit test that exposes either a software requirement or a defect. This test will fail because either the requirement isn't implemented yet, or because it intentionally exposes a defect in the existing code. Then, the developer writes the simplest code to make the test, along with other tests, pass.

Most code in a system is unit tested, but not necessarily all paths through the code. Extreme programming mandates a "test everything that can possibly break" strategy, over the traditional "test every execution path" method. This leads developers to develop fewer tests than classical methods, but this isn't really a problem, more a restatement of fact, as classical methods have rarely ever been followed methodically enough for all execution paths to have been thoroughly tested.{{Citation needed|date=November 2008}} Extreme programming simply recognizes that testing is rarely exhaustive (because it is often too expensive and time-consuming to be economically viable) and provides guidance on how to effectively focus limited resources.

Crucially, the test code is considered a first class project artifact in that it is maintained at the same quality as the implementation code, with all duplication removed. Developers release unit testing code to the code repository in conjunction with the code it tests. Extreme programming's thorough unit testing allows the benefits mentioned above, such as simpler and more confident code development and refactoring, simplified code integration, accurate documentation, and more modular designs. These unit tests are also constantly run as a form of regression test.

Unit testing is also critical to the concept of Emergent Design. As emergent design is heavily dependent upon refactoring, unit tests are an integral component.{{cn|date=November 2023}}

An automated testing framework provides features for automating test execution and can accelerate writing and running tests. Frameworks have been developed for a wide variety of programming languages.

Generally, frameworks are third-party; not distributed with a compiler or integrated development environment (IDE).

Tests can be written without using a framework to exercise the code under test using assertions, exception handling, and other control flow mechanisms to verify behavior and report failure. Some note that testing without a framework is valuable since there is a barrier to entry for the adoption of a framework; that having some tests is better than none, but once a framework is in place, adding tests can be easier.{{cite web|url=http://www.bullseye.com/coverage.html|access-date=24 March 2009|title=Intermediate Coverage Goals|author=Bullseye Testing Technology|date=2006–2008}}

In some frameworks advanced test features are missing and must be hand-coded.

Some programming languages directly support unit testing. Their grammar allows the direct declaration of unit tests without importing a library (whether third party or standard). Additionally, the Boolean conditions of the unit tests can be expressed in the same syntax as Boolean expressions used in non-unit test code, such as what is used for {{code| lang = java |if}} and {{code| lang = java |while}} statements.

Languages with built-in unit testing support include:

{{colbegin|colwidth=20em}}

• Cobra
• D{{cite web|title=Unit Tests - D Programming Language|url=http://dlang.org/spec/unittest.html|website=D Programming Language|publisher=D Language Foundation|access-date=5 August 2017}}
• Rust{{cite web|url=https://doc.rust-lang.org/book/ch11-01-writing-tests.html|access-date=21 August 2023|title=How to Write Tests|author=Steve Klabnik and Carol Nichols, with contributions from the Rust Community|date=2015–2023}}

{{colend}}

Languages with standard unit testing framework support include:

{{colbegin|colwidth=20em}}

• Apex
• Crystal{{cite web|url=https://crystal-lang.org/api/0.23.1/Spec.html|access-date=18 September 2017|title=Crystal Spec|publisher=crystal-lang.org}}
• Erlang
• Go{{cite web|url=http://golang.org/pkg/testing/|access-date=3 December 2013|title=testing - The Go Programming Language|publisher=golang.org}}
• Julia{{cite web|url=https://docs.julialang.org/en/v1/stdlib/Test/|title=Unit Testing · The Julia Language|access-date=2022-06-15|publisher=docs.julialang.org}}
• LabVIEW
• MATLAB
• Python{{cite web|url=https://docs.python.org/3/library/unittest.html|access-date=18 April 2016|title=unittest -- Unit testing framework|author=Python Documentation|date=2016}}
• Racket{{cite web|last1=Welsh|first1=Noel|last2=Culpepper|first2=Ryan|title=RackUnit: Unit Testing|url=http://docs.racket-lang.org/rackunit/index.html|publisher=PLT Design Inc.|access-date=26 February 2019|ref=Racket_Unit_Testing}}{{cite web|last1=Welsh|first1=Noel|last2=Culpepper|first2=Ryan|title=RackUnit Unit Testing package part of Racket main distribution|url=https://pkgs.racket-lang.org/package/rackunit|publisher=PLT Design Inc.|access-date=26 February 2019|ref=Racket_Unit_Testing_Main_dist}}
• Ruby{{cite web|url=http://ruby-doc.org/stdlib-2.0.0/libdoc/minitest/rdoc/MiniTest.html|title=Minitest (Ruby 2.0)|publisher=Ruby-Doc.org}}
• Swift

{{colend}}

Some languages do not have built-in unit-testing support but have established unit testing libraries or frameworks. These languages include:

{{colbegin|colwidth=20em}}

• ABAP
• C++
• C#
• Clojure{{cite web|last1=Sierra|first1=Stuart|title=API for clojure.test - Clojure v1.6 (stable)|url=https://clojure.github.io/clojure/clojure.test-api.html|access-date=11 February 2015|ref=Clojure_Unit_Testing_Framework}}
• Elixir
• Java
• JavaScript
• Objective-C
• Perl
• PHP
• PowerShell{{cite web|url=https://github.com/pester/Pester|access-date=28 January 2016|title=Pester Framework|website=GitHub}}
• R with testthat
• Scala
• tcl
• Visual Basic .NET
• Xojo with XojoUnit

{{colend}}

{{colbegin|colwidth=20em}}

• Acceptance testing
• Characterization test
• Component-based usability testing
• Design predicates
• Design by contract
• Extreme programming
• Functional testing
• Integration testing
• List of unit testing frameworks
• Regression testing
• Software archaeology
• Software testing
• System testing
• Test case
• Test-driven development
• xUnit – a family of unit testing frameworks.

{{colend}}

{{Reflist}}

• {{cite book |last1=Feathers |first1=Michael C. |title=Working Effectively with Legacy Code |date=2005 |publisher=Prentice Hall Professional Technical Reference |location=Upper Saddle River, NJ |isbn=978-0131177055}}
• {{cite book

| last1 = Gulati

| first1 = Shekhar

| last2 = Sharma

| first2 = Rahul

| title = Java Unit Testing with JUnit 5

| publisher = Apress

| year = 2017

}}

• [http://c2.com/cgi/wiki?TestDrivenDevelopment Test Driven Development (Ward Cunningham's Wiki)]

{{Software testing}}

{{DEFAULTSORT:Unit Testing}}

Category:Extreme programming

Category:Articles with example Java code

Category:Types of tools used in software development