Regression test case selection & prioritization using dependence graph and genetic algorithm
Regression testing is very important process in software maintenance. Unfortunately, it is costly and time consuming to allow for the re-execution of all test cases during regression testing. The challenge in regression testing is the selection of best test cases from the existing test suite.This pa...
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| Format: | Article |
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International Organization of Scientific Research
2014
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| Online Access: | http://psasir.upm.edu.my/id/eprint/35193/ |
| _version_ | 1848847986319163392 |
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| author | Musa, Samaila Md Sultan, Abu Bakar Abd Ghani, Abdul Azim Baharom, Salmi |
| author_facet | Musa, Samaila Md Sultan, Abu Bakar Abd Ghani, Abdul Azim Baharom, Salmi |
| author_sort | Musa, Samaila |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Regression testing is very important process in software maintenance. Unfortunately, it is costly and time consuming to allow for the re-execution of all test cases during regression testing. The challenge in regression testing is the selection of best test cases from the existing test suite.This paper presents an evolutionary regression test case prioritization for object-oriented software based on extended system dependence graph model of the affected program using genetic algorithm. The approach is based on optimization of selected test case from dependency analysis of the source codes. The goal is to identify changes in a method's body due to data dependence, control dependence and dependent due to object relation such as inheritance and polymorphism, select the test cases based on affected statements and ordered them based on their fitness by using GA.The number of affected statements determined how fit a test case is good for regression testing. A case study is reported to provide evidence of the feasibility of the approach and its benefits in increasing the rate of fault detection and reduction in regression testing effort compared with retest-all. It was shown that our approach needs 30% of the test cases to cover all the faults, while 80% is needed to cover all the faults using retest-all, which is time consuming and costly. |
| first_indexed | 2025-11-15T09:27:19Z |
| format | Article |
| id | upm-35193 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T09:27:19Z |
| publishDate | 2014 |
| publisher | International Organization of Scientific Research |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-351932015-12-31T02:31:57Z http://psasir.upm.edu.my/id/eprint/35193/ Regression test case selection & prioritization using dependence graph and genetic algorithm Musa, Samaila Md Sultan, Abu Bakar Abd Ghani, Abdul Azim Baharom, Salmi Regression testing is very important process in software maintenance. Unfortunately, it is costly and time consuming to allow for the re-execution of all test cases during regression testing. The challenge in regression testing is the selection of best test cases from the existing test suite.This paper presents an evolutionary regression test case prioritization for object-oriented software based on extended system dependence graph model of the affected program using genetic algorithm. The approach is based on optimization of selected test case from dependency analysis of the source codes. The goal is to identify changes in a method's body due to data dependence, control dependence and dependent due to object relation such as inheritance and polymorphism, select the test cases based on affected statements and ordered them based on their fitness by using GA.The number of affected statements determined how fit a test case is good for regression testing. A case study is reported to provide evidence of the feasibility of the approach and its benefits in increasing the rate of fault detection and reduction in regression testing effort compared with retest-all. It was shown that our approach needs 30% of the test cases to cover all the faults, while 80% is needed to cover all the faults using retest-all, which is time consuming and costly. International Organization of Scientific Research 2014 Article PeerReviewed Musa, Samaila and Md Sultan, Abu Bakar and Abd Ghani, Abdul Azim and Baharom, Salmi (2014) Regression test case selection & prioritization using dependence graph and genetic algorithm. IOSR Journal of Computer Engineering, 16 (3). pp. 38-47. ISSN 2278-8727; ESSN: 2278-0661 http://iosrjournals.org/iosr-jce/pages/16%283%29Version-4.html 10.9790/0661-16343847 |
| spellingShingle | Musa, Samaila Md Sultan, Abu Bakar Abd Ghani, Abdul Azim Baharom, Salmi Regression test case selection & prioritization using dependence graph and genetic algorithm |
| title | Regression test case selection & prioritization using dependence graph and genetic algorithm |
| title_full | Regression test case selection & prioritization using dependence graph and genetic algorithm |
| title_fullStr | Regression test case selection & prioritization using dependence graph and genetic algorithm |
| title_full_unstemmed | Regression test case selection & prioritization using dependence graph and genetic algorithm |
| title_short | Regression test case selection & prioritization using dependence graph and genetic algorithm |
| title_sort | regression test case selection & prioritization using dependence graph and genetic algorithm |
| url | http://psasir.upm.edu.my/id/eprint/35193/ http://psasir.upm.edu.my/id/eprint/35193/ http://psasir.upm.edu.my/id/eprint/35193/ |