Michel Maes-Bermejo, Alexander Serebrenik, Micael Gallego, Francisco Gortázar, Gregorio Robles, Jesús María González Barahona
{"title":"寻找错误：通过回归测试自动识别导致错误的变更","authors":"Michel Maes-Bermejo, Alexander Serebrenik, Micael Gallego, Francisco Gortázar, Gregorio Robles, Jesús María González Barahona","doi":"10.1007/s10664-024-10479-z","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Context</h3><p>Finding code changes that introduced bugs is important both for practitioners and researchers, but doing it precisely is a manual, effort-intensive process. The <i>perfect test</i> method is a theoretical construct aimed at detecting Bug-Introducing Changes (BIC) through a theoretical <i>perfect test</i>. This <i>perfect test</i> always fails if the bug is present, and passes otherwise.</p><h3 data-test=\"abstract-sub-heading\">Objective</h3><p>To explore a possible automatic operationalization of the <i>perfect test</i> method.</p><h3 data-test=\"abstract-sub-heading\">Method</h3><p>To use regression tests as substitutes for the <i>perfect test</i>. For this, we transplant the regression tests to past snapshots of the code, and use them to identify the BIC, on a well-known collection of bugs from the Defects4J dataset.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>From 809 bugs in the dataset, when running our operationalization of the perfect test method, for 95 of them the BIC was identified precisely and in the remaining 4 cases, a list of candidates including the BIC was provided.</p><h3 data-test=\"abstract-sub-heading\">Conclusions</h3><p>We demonstrate that the operationalization of the <i>perfect test</i> method through regression tests is feasible and can be completely automated in practice when tests can be transplanted and run in past snapshots of the code. Given that implementing regression tests when a bug is fixed is considered a good practice, when developers follow it, they can detect effortlessly bug-introducing changes by using our operationalization of the <i>perfect test</i> method.</p>","PeriodicalId":11525,"journal":{"name":"Empirical Software Engineering","volume":"1 1","pages":""},"PeriodicalIF":3.5000,"publicationDate":"2024-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hunting bugs: Towards an automated approach to identifying which change caused a bug through regression testing\",\"authors\":\"Michel Maes-Bermejo, Alexander Serebrenik, Micael Gallego, Francisco Gortázar, Gregorio Robles, Jesús María González Barahona\",\"doi\":\"10.1007/s10664-024-10479-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<h3 data-test=\\\"abstract-sub-heading\\\">Context</h3><p>Finding code changes that introduced bugs is important both for practitioners and researchers, but doing it precisely is a manual, effort-intensive process. The <i>perfect test</i> method is a theoretical construct aimed at detecting Bug-Introducing Changes (BIC) through a theoretical <i>perfect test</i>. This <i>perfect test</i> always fails if the bug is present, and passes otherwise.</p><h3 data-test=\\\"abstract-sub-heading\\\">Objective</h3><p>To explore a possible automatic operationalization of the <i>perfect test</i> method.</p><h3 data-test=\\\"abstract-sub-heading\\\">Method</h3><p>To use regression tests as substitutes for the <i>perfect test</i>. 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Hunting bugs: Towards an automated approach to identifying which change caused a bug through regression testing
Context
Finding code changes that introduced bugs is important both for practitioners and researchers, but doing it precisely is a manual, effort-intensive process. The perfect test method is a theoretical construct aimed at detecting Bug-Introducing Changes (BIC) through a theoretical perfect test. This perfect test always fails if the bug is present, and passes otherwise.
Objective
To explore a possible automatic operationalization of the perfect test method.
Method
To use regression tests as substitutes for the perfect test. For this, we transplant the regression tests to past snapshots of the code, and use them to identify the BIC, on a well-known collection of bugs from the Defects4J dataset.
Results
From 809 bugs in the dataset, when running our operationalization of the perfect test method, for 95 of them the BIC was identified precisely and in the remaining 4 cases, a list of candidates including the BIC was provided.
Conclusions
We demonstrate that the operationalization of the perfect test method through regression tests is feasible and can be completely automated in practice when tests can be transplanted and run in past snapshots of the code. Given that implementing regression tests when a bug is fixed is considered a good practice, when developers follow it, they can detect effortlessly bug-introducing changes by using our operationalization of the perfect test method.
期刊介绍：
Empirical Software Engineering provides a forum for applied software engineering research with a strong empirical component, and a venue for publishing empirical results relevant to both researchers and practitioners. Empirical studies presented here usually involve the collection and analysis of data and experience that can be used to characterize, evaluate and reveal relationships between software development deliverables, practices, and technologies. Over time, it is expected that such empirical results will form a body of knowledge leading to widely accepted and well-formed theories.
The journal also offers industrial experience reports detailing the application of software technologies - processes, methods, or tools - and their effectiveness in industrial settings.
Empirical Software Engineering promotes the publication of industry-relevant research, to address the significant gap between research and practice.
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