Natural optimization algorithms for optimal regression testing
The optimal regression testing problem is that of determining the minimum number of test cases needed for revalidating modified software in the maintenance phase. The present two natural optimization algorithms, namely simulated annealing and genetic algorithms, for solving this problem. The algorit...
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1997
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| Online Access: | http://hdl.handle.net/10725/7929 http://dx.doi.org/10.1109/CMPSAC.1997.625060 http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://ieeexplore.ieee.org/abstract/document/625060/ |
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| _version_ | 1864513483483119619 |
|---|---|
| author | Mansour, Nashat |
| author_facet | Mansour, Nashat |
| author_role | author |
| dc.creator.none.fl_str_mv | Mansour, Nashat |
| dc.date.none.fl_str_mv | 1997 2018-05-24T06:12:59Z 2018-05-24T06:12:59Z 2018-05-24 |
| dc.identifier.none.fl_str_mv | 0-8186-8105-5 http://hdl.handle.net/10725/7929 http://dx.doi.org/10.1109/CMPSAC.1997.625060 Mansour, P., & El-Fakih, K. (1997, August). Natural optimization algorithms for optimal regression testing. In Computer Software and Applications Conference, 1997. COMPSAC'97. Proceedings., The Twenty-First Annual International (pp. 511-514). IEEE. http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://ieeexplore.ieee.org/abstract/document/625060/ |
| dc.language.none.fl_str_mv | en |
| dc.publisher.none.fl_str_mv | IEEE Xplore |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.title.none.fl_str_mv | Natural optimization algorithms for optimal regression testing |
| dc.type.none.fl_str_mv | Conference Paper / Proceeding info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/conferenceObject |
| description | The optimal regression testing problem is that of determining the minimum number of test cases needed for revalidating modified software in the maintenance phase. The present two natural optimization algorithms, namely simulated annealing and genetic algorithms, for solving this problem. The algorithms are based on an integer programming problem formulation and the program's control-flow graph. The main advantage of these algorithms is that they do not suffer from exponential explosion for realistic program sizes. The experimental results show that they find optimal or near-optimal number of retests in a reasonable time. |
| eu_rights_str_mv | openAccess |
| format | conferenceObject |
| id | LAURepo_9ed45dc78f5cb2f40b3d9400da3b5f71 |
| identifier_str_mv | 0-8186-8105-5 Mansour, P., & El-Fakih, K. (1997, August). Natural optimization algorithms for optimal regression testing. In Computer Software and Applications Conference, 1997. COMPSAC'97. Proceedings., The Twenty-First Annual International (pp. 511-514). IEEE. |
| language_invalid_str_mv | en |
| network_acronym_str | LAURepo |
| network_name_str | Lebanese American University repository |
| oai_identifier_str | oai:laur.lau.edu.lb:10725/7929 |
| publishDate | 1997 |
| publisher.none.fl_str_mv | IEEE Xplore |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Natural optimization algorithms for optimal regression testingMansour, NashatThe optimal regression testing problem is that of determining the minimum number of test cases needed for revalidating modified software in the maintenance phase. The present two natural optimization algorithms, namely simulated annealing and genetic algorithms, for solving this problem. The algorithms are based on an integer programming problem formulation and the program's control-flow graph. The main advantage of these algorithms is that they do not suffer from exponential explosion for realistic program sizes. The experimental results show that they find optimal or near-optimal number of retests in a reasonable time.N/AIEEE Xplore2018-05-24T06:12:59Z2018-05-24T06:12:59Z19972018-05-24Conference Paper / Proceedinginfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject0-8186-8105-5http://hdl.handle.net/10725/7929http://dx.doi.org/10.1109/CMPSAC.1997.625060Mansour, P., & El-Fakih, K. (1997, August). Natural optimization algorithms for optimal regression testing. In Computer Software and Applications Conference, 1997. COMPSAC'97. Proceedings., The Twenty-First Annual International (pp. 511-514). IEEE.http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.phphttps://ieeexplore.ieee.org/abstract/document/625060/eninfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/79292021-03-19T10:43:14Z |
| spellingShingle | Natural optimization algorithms for optimal regression testing Mansour, Nashat |
| status_str | publishedVersion |
| title | Natural optimization algorithms for optimal regression testing |
| title_full | Natural optimization algorithms for optimal regression testing |
| title_fullStr | Natural optimization algorithms for optimal regression testing |
| title_full_unstemmed | Natural optimization algorithms for optimal regression testing |
| title_short | Natural optimization algorithms for optimal regression testing |
| title_sort | Natural optimization algorithms for optimal regression testing |
| url | http://hdl.handle.net/10725/7929 http://dx.doi.org/10.1109/CMPSAC.1997.625060 http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://ieeexplore.ieee.org/abstract/document/625060/ |