Reduction-based methods and metrics for selective regression testing

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dc.contributor.author Mansour, Nashat
dc.contributor.author Bahsoon, Rami
dc.date.accessioned 2016-01-26T08:10:12Z
dc.date.available 2016-01-26T08:10:12Z
dc.date.copyright 2002
dc.date.issued 2016-01-26
dc.identifier.issn 0950-5849 en_US
dc.identifier.uri http://hdl.handle.net/10725/2953
dc.description.abstract In corrective maintenance, modified software is regression tested using selected test cases in order to ensure that the modifications have not caused adverse effects. This activity of selective regression testing involves regression test selection, which refers to selecting test cases from the previously run test suite, and test-coverage identification. In this paper, we propose three test-selection methods and two coverage identification metrics. The three methods aim to reduce the number of selected test cases for retesting the modified software. The first method, referred to as modification-based reduction version 1 (MBR1), selects a reduced number of test cases based on the modification made and its effects in the software. The second method, referred to as modification-based reduction version 2 (MBR2) improves MBR1 by further omitting tests that do not cover the modification. The third method, referred to as precise reduction (PR), reduces the number of test cases selected by omitting non-modification-revealing tests from the initial test suite. The two coverage metrics are McCabe-based regression test metrics, which are referred to as the Reachability regression Test selection McCabe-based metric (RTM), and data-flow Slices regression Test McCabe-based metric (STM). These metrics aim to assist the regression tester in monitoring test-coverage adequacy, reveal any shortage or redundancy in the test suite, and assist in identifying, where additional tests may be required for regression testing. We empirically compare MBR1, MBR2, and PR with three reduction and precision-oriented methods on 60 test-problems. The results show that PR selects the least number of test cases most of the time and omits non-modification-revealing tests. We also demonstrate the applicability of our proposed methods to object-oriented regression testing at the class level. Further, we illustrate typical application of the RTM and STM metrics using the 60 test-problems and two coverage-oriented selective regression-testing methods. en_US
dc.language.iso en en_US
dc.title Reduction-based methods and metrics for selective regression testing en_US
dc.type Article en_US
dc.description.version Published en_US
dc.author.school SAS en_US
dc.author.idnumber 198629170 en_US
dc.author.woa N/A en_US
dc.author.department Computer Science and Mathematics en_US
dc.description.embargo N/A en_US
dc.relation.journal Information and Software Technology en_US
dc.journal.volume 44 en_US
dc.journal.issue 7 en_US
dc.article.pages 431-443 en_US
dc.keywords Object-oriented regression testing en_US
dc.keywords Regression testing metrics en_US
dc.keywords Selective regression testing en_US
dc.keywords Software engineering en_US
dc.keywords Software maintenance en_US
dc.keywords Test coverage en_US
dc.identifier.doi http://dx.doi.org/10.1016/S0950-5849(02)00027-7 en_US
dc.identifier.ctation Mansour, N., & Bahsoon, R. (2002). Reduction-based methods and metrics for selective regression testing. Information and Software Technology, 44(7), 431-443. en_US
dc.author.email mansour@lau.edu.lb
dc.identifier.url http://www.sciencedirect.com/science/article/pii/S0950584902000277

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