Software regression

Techniques have been proposed that try to prevent regressions from being introduced into software at various stages of development, as outlined below.

{{main|Regression testing}}

In order to avoid regressions being seen by the end-user after release, developers regularly run regression tests after changes are introduced to the software. These tests can include unit tests to catch local regressions as well as integration tests to catch remote regressions.{{cite book |last1=Leung |first1=Hareton K.N. |last2=White |first2=Lee |title=Proceedings of the International Conference on Software Maintenance |date=November 1990 |publisher=IEEE |location=San Diego, CA, USA |isbn=0-8186-2091-9 |url=https://ieeexplore.ieee.org/document/131377 |chapter=A study of integration testing and software regression at the integration level|doi=10.1109/ICSM.1990.131377 |s2cid=62583582 }} Regression testing techniques often leverage existing test cases to minimize the effort involved in creating them.{{cite journal |last1=Rothermel |first1=Gregg |last2=Harrold |first2=Mary Jean |last3=Dedhia |first3=Jeinay |title=Regression test selection for C++ software |journal=Software Testing, Verification and Reliability |date=2000 |volume=10 |issue=2 |pages=77–109 |doi=10.1002/1099-1689(200006)10:2<77::AID-STVR197>3.0.CO;2-E |url=https://onlinelibrary.wiley.com/doi/abs/10.1002/1099-1689(200006)10:2%3C77::AID-STVR197%3E3.0.CO;2-E |language=en |issn=1099-1689|url-access=subscription }} However, due to the volume of these existing tests, it is often necessary to select a representative subset, using techniques such as test-case prioritization.

For detecting performance regressions, software performance tests are run on a regular basis, to monitor the response time and resource usage metrics of the software after subsequent changes.{{cite journal |last1=Weyuker |first1=E.J. |last2=Vokolos |first2=F.I. |title=Experience with performance testing of software systems: issues, an approach, and case study |journal=IEEE Transactions on Software Engineering |date=December 2000 |volume=26 |issue=12 |pages=1147–1156 |doi=10.1109/32.888628 |url=https://ieeexplore.ieee.org/document/888628 |issn=1939-3520|url-access=subscription }} Unlike functional regression tests, the results of performance tests are subject to variance - that is, results can differ between tests due to variance in performance measurements; as a result, a decision must be made on whether a change in performance numbers constitutes a regression, based on experience and end-user demands. Approaches such as statistical significance testing and change point detection are sometimes used to aid in this decision.{{cite book |last1=Daly |first1=David |last2=Brown |first2=William |last3=Ingo |first3=Henrik |last4=O'Leary |first4=Jim |last5=Bradford |first5=David |title=Proceedings of the International Conference on Performance Engineering |date=20 April 2020 |publisher=Association for Computing Machinery |isbn=978-1-4503-6991-6 |pages=67–75 |url=https://dl.acm.org/doi/abs/10.1145/3358960.3375791 |chapter=The Use of Change Point Detection to Identify Software Performance Regressions in a Continuous Integration System|doi=10.1145/3358960.3375791 |s2cid=211677818 }}

Since debugging and localizing the root cause of a software regression can be expensive,{{cite book |last1=Nistor |first1=Adrian |last2=Jiang |first2=Tian |last3=Tan |first3=Lin |title=Proceedings of the Working Conference on Mining Software Repositories (MSR) |date=May 2013 |pages=237–246 |url=https://ieeexplore.ieee.org/document/6624035 |chapter=Discovering, reporting, and fixing performance bugs|doi=10.1109/MSR.2013.6624035 |isbn=978-1-4673-2936-1 |s2cid=12773088 }}{{cite journal |last1=Agarwal |first1=Pragya |last2=Agrawal |first2=Arun Prakash |title=Fault-localization techniques for software systems: a literature review |journal=ACM SIGSOFT Software Engineering Notes |date=17 September 2014 |volume=39 |issue=5 |pages=1–8 |doi=10.1145/2659118.2659125 |s2cid=12101263 |url=https://dl.acm.org/doi/abs/10.1145/2659118.2659125 |issn=0163-5948|url-access=subscription }} there also exist some methods that try to prevent regressions from being committed into the code repository in the first place. For example, Git Hooks enable developers to run test scripts before code changes are committed or pushed to the code repository.{{cite web |title=Git - Git Hooks |url=https://git-scm.com/book/en/v2/Customizing-Git-Git-Hooks |website=git-scm.com |access-date=7 November 2021}} In addition, change impact analysis has been applied to software to predict the impact of a code change on various components of the program, and to supplement test case selection and prioritization.{{cite journal |last1=Orso |first1=Alessandro |last2=Apiwattanapong |first2=Taweesup |last3=Harrold |first3=Mary Jean |title=Leveraging field data for impact analysis and regression testing |journal=ACM SIGSOFT Software Engineering Notes |date=1 September 2003 |volume=28 |issue=5 |pages=128–137 |doi=10.1145/949952.940089 |url=https://dl.acm.org/doi/abs/10.1145/949952.940089 |issn=0163-5948|url-access=subscription }}{{cite book |last1=Qu |first1=Xiao |last2=Acharya |first2=Mithun |last3=Robinson |first3=Brian |title=Proceedings of the International Conference on Software Maintenance |date=September 2012 |pages=129–138 |url=https://ieeexplore.ieee.org/document/6405263 |chapter=Configuration selection using code change impact analysis for regression testing|doi=10.1109/ICSM.2012.6405263 |isbn=978-1-4673-2312-3 |s2cid=14928793 }} Software linters are also often added to commit hooks to ensure consistent coding style, thereby minimizing stylistic issues that can make the software prone to regressions.{{cite book |last1=Tómasdóttir |first1=Kristín Fjóla |last2=Aniche |first2=Mauricio |last3=van Deursen |first3=Arie |title=Proceedings of the International Conference on Automated Software Engineering |date=October 2017 |pages=578–589 |url=https://ieeexplore.ieee.org/document/8115668 |chapter=Why and how JavaScript developers use linters|doi=10.1109/ASE.2017.8115668 |isbn=978-1-5386-2684-9 |s2cid=215750004 }}

Many of the techniques used to find the root cause of non-regression software bugs can also be used to debug software regressions, including breakpoint debugging, print debugging, and program slicing. The techniques described below are often used specifically to debug software regressions.

A common technique used to localize functional regressions is bisection, which takes both a buggy commit and a previously working commit as input, and tries to find the root cause by doing a binary search on the commits in between.{{cite book |last1=Gross |first1=Thomas |title=Proceedings of the International Workshop on Automatic Debugging |date=10 September 1997 |publisher=Linkøping University Electronic Press |pages=185–191 |url=https://ep.liu.se/en/conference-article.aspx?series=ecp&issue=1&Article_No=15 |language=en |chapter=Bisection Debugging}} Version control systems such as Git and Mercurial provide built-in ways to perform bisection on a given pair of commits.{{cite web |title=Git - git-bisect Documentation |url=https://git-scm.com/docs/git-bisect |website=git-scm.com |access-date=7 November 2021}}{{cite web |title=hg - bisect |url=https://www.selenic.com/mercurial/hg.1.html |website=www.selenic.com |publisher=Mercurial |access-date=7 November 2021}}

Other options include directly associating the result of a regression test with code changes;{{cite web |title=Reading 11: Debugging |url=https://web.mit.edu/6.005/www/fa15/classes/11-debugging/ |website=web.mit.edu |publisher=MIT}} setting divergence breakpoints;{{cite book |last1=Buhse |first1=Ben |last2=Wei |first2=Thomas |last3=Zang |first3=Zhiqiang |last4=Milicevic |first4=Aleksandar |last5=Gligoric |first5=Milos |title=Proceedings of the International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) |date=May 2019 |pages=15–18 |url=https://ieeexplore.ieee.org/document/8802682 |chapter=VeDebug: Regression Debugging Tool for Java|doi=10.1109/ICSE-Companion.2019.00027 |isbn=978-1-7281-1764-5 |s2cid=174799830 }} or using incremental data-flow analysis, which identifies test cases - including failing ones - that are relevant to a set of code changes,{{cite book |last1=Taha |first1=A.-B. |last2=Thebaut |first2=S.M. |last3=Liu |first3=S.-S. |title=Proceedings of the Annual International Computer Software & Applications Conference |date=September 1989 |publisher=IEEE |pages=527–534 |url=https://ieeexplore.ieee.org/document/65142 |chapter=An approach to software fault localization and revalidation based on incremental data flow analysis|doi=10.1109/CMPSAC.1989.65142 |isbn=0-8186-1964-3 |s2cid=41978046 }} among others.

Profiling measures the performance and resource usage of various components of a program, and is used to generate data useful in debugging performance issues. In the context of software performance regressions, developers often compare the call trees (also known as "timelines") generated by profilers for both the buggy version and the previously working version, and mechanisms exist to simplify this comparison.{{cite journal |last1=Ocariza |first1=Frolin S. |last2=Zhao |first2=Boyang |title=Localizing software performance regressions in web applications by comparing execution timelines |journal=Software Testing, Verification and Reliability |date=2021 |volume=31 |issue=5 |pages=e1750 |doi=10.1002/stvr.1750 |s2cid=225416138 |url=https://onlinelibrary.wiley.com/doi/abs/10.1002/stvr.1750 |language=en |issn=1099-1689|url-access=subscription }} Web development tools typically provide developers the ability to record these performance profiles.{{cite web |title=Analyze runtime performance |url=https://developer.chrome.com/docs/devtools/evaluate-performance/ |website=Chrome Developers |publisher=Google |access-date=7 November 2021 |language=en}}{{cite web |title=Performance analysis reference - Microsoft Edge Development |url=https://docs.microsoft.com/en-us/microsoft-edge/devtools-guide-chromium/evaluate-performance/reference |website=docs.microsoft.com |publisher=Microsoft |access-date=7 November 2021 |language=en-us}}

Logging also helps with performance regression localization, and similar to call trees, developers can compare systematically-placed performance logs of multiple versions of the same software.{{cite book |last1=Yao |first1=Kundi |last2=B. de Pádua |first2=Guilherme |last3=Shang |first3=Weiyi |last4=Sporea |first4=Steve |last5=Toma |first5=Andrei |last6=Sajedi |first6=Sarah |title=Proceedings of the International Conference on Performance Engineering |date=30 March 2018 |publisher=Association for Computing Machinery |isbn=978-1-4503-5095-2 |pages=127–138 |url=https://dl.acm.org/doi/abs/10.1145/3184407.3184416 |chapter=Log4Perf: Suggesting Logging Locations for Web-based Systems' Performance Monitoring|doi=10.1145/3184407.3184416 |s2cid=4557038 }} A tradeoff exists when adding these performance logs, as adding many logs can help developers pinpoint which portions of the software are regressing at smaller granularities, while adding only a few logs will also reduce overhead when executing the program.{{cite journal |title=A Qualitative Study of the Benefits and Costs of Logging from Developers' Perspectives |journal=IEEE Transactions on Software Engineering |date=30 January 2020 |doi=10.1109/TSE.2020.2970422 |url=https://ieeexplore.ieee.org/document/8976297|last1=Li |first1=Heng |last2=Shang |first2=Weiyi |last3=Adams |first3=Bram |last4=Sayagh |first4=Mohammed |last5=Hassan |first5=Ahmed E. |volume=47 |issue=12 |pages=2858–2873 |s2cid=213679706 |url-access=subscription }}

Additional approaches include writing performance-aware unit tests to help with localization,{{cite book |last1=Heger |first1=Christoph |last2=Happe |first2=Jens |last3=Farahbod |first3=Roozbeh |title=Proceedings of the International Conference on Performance Engineering |date=21 April 2013 |publisher=Association for Computing Machinery |isbn=978-1-4503-1636-1 |pages=27–38 |url=https://dl.acm.org/doi/abs/10.1145/2479871.2479879 |chapter=Automated root cause isolation of performance regressions during software development|doi=10.1145/2479871.2479879 |s2cid=2593603 }} and ranking subsystems based on performance counter deviations.{{cite book |last1=Malik |first1=Haroon |last2=Adams |first2=Bram |last3=Hassan |first3=Ahmed E. |title=Proceedings of the International Symposium on Software Reliability Engineering |date=November 2010 |pages=201–210 |url=https://ieeexplore.ieee.org/document/5635038 |chapter=Pinpointing the Subsystems Responsible for the Performance Deviations in a Load Test|doi=10.1109/ISSRE.2010.43 |isbn=978-1-4244-9056-1 |s2cid=17306870 }} Bisection can also be repurposed for performance regressions by considering commits that perform below (or above) a certain baseline value as buggy, and taking either the left or the right side of the commits based on the results of this comparison.

• Software rot
• Software aging

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Category:Software bugs