Data Generation for Path Testing
We present two stochastic search algorithms for generating test cases that execute specified paths in a program. The two algorithms are: a simulated annealing algorithm (SA), and a genetic algorithm (GA). These algorithms are based on an optimization formulation of the path testing problem which inc...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | |
| التنسيق: | article |
| منشور في: |
2004
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| الوصول للمادة أونلاين: | http://hdl.handle.net/10725/2967 http://dx.doi.org/10.1023/B:SQJO.0000024059.72478.4e http://link.springer.com/article/10.1023/B:SQJO.0000024059.72478.4e |
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| _version_ | 1864513459740213248 |
|---|---|
| author | Mansour, Nashat |
| author2 | Salame, Miran |
| author2_role | author |
| author_facet | Mansour, Nashat Salame, Miran |
| author_role | author |
| dc.creator.none.fl_str_mv | Mansour, Nashat Salame, Miran |
| dc.date.none.fl_str_mv | 2004 2016-01-27T09:16:42Z 2016-01-27T09:16:42Z 2016-01-27 |
| dc.identifier.none.fl_str_mv | 0963-9314 http://hdl.handle.net/10725/2967 http://dx.doi.org/10.1023/B:SQJO.0000024059.72478.4e Mansour, N., & Salame, M. (2004). Data generation for path testing. Software Quality Journal, 12(2), 121-136. http://link.springer.com/article/10.1023/B:SQJO.0000024059.72478.4e |
| dc.language.none.fl_str_mv | en |
| dc.relation.none.fl_str_mv | Software Quality Journal |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.title.none.fl_str_mv | Data Generation for Path Testing |
| dc.type.none.fl_str_mv | Article info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | We present two stochastic search algorithms for generating test cases that execute specified paths in a program. The two algorithms are: a simulated annealing algorithm (SA), and a genetic algorithm (GA). These algorithms are based on an optimization formulation of the path testing problem which include both integer- and real-value test cases. We empirically compare the SA and GA algorithms with each other and with a hill-climbing algorithm, Korel's algorithm (KA), for integer-value-input subject programs and compare SA and GA with each other on real-value subject programs. Our empirical work uses several subject programs with a number of paths. The results show that: (a) SA and GA are superior to KA in the number of executed paths, (b) SA tends to perform slightly better than GA in terms of the number of executed paths, and (c) GA is faster than SA; however, KA, when it succeeds in finding the solution, is the fastest. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | LAURepo_43f4dab225abfe83e980256b7fcbe404 |
| identifier_str_mv | 0963-9314 Mansour, N., & Salame, M. (2004). Data generation for path testing. Software Quality Journal, 12(2), 121-136. |
| language_invalid_str_mv | en |
| network_acronym_str | LAURepo |
| network_name_str | Lebanese American University repository |
| oai_identifier_str | oai:laur.lau.edu.lb:10725/2967 |
| publishDate | 2004 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Data Generation for Path TestingMansour, NashatSalame, MiranWe present two stochastic search algorithms for generating test cases that execute specified paths in a program. The two algorithms are: a simulated annealing algorithm (SA), and a genetic algorithm (GA). These algorithms are based on an optimization formulation of the path testing problem which include both integer- and real-value test cases. We empirically compare the SA and GA algorithms with each other and with a hill-climbing algorithm, Korel's algorithm (KA), for integer-value-input subject programs and compare SA and GA with each other on real-value subject programs. Our empirical work uses several subject programs with a number of paths. The results show that: (a) SA and GA are superior to KA in the number of executed paths, (b) SA tends to perform slightly better than GA in terms of the number of executed paths, and (c) GA is faster than SA; however, KA, when it succeeds in finding the solution, is the fastest.PublishedN/A2016-01-27T09:16:42Z2016-01-27T09:16:42Z20042016-01-27Articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article0963-9314http://hdl.handle.net/10725/2967http://dx.doi.org/10.1023/B:SQJO.0000024059.72478.4eMansour, N., & Salame, M. (2004). Data generation for path testing. Software Quality Journal, 12(2), 121-136.http://link.springer.com/article/10.1023/B:SQJO.0000024059.72478.4eenSoftware Quality Journalinfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/29672017-04-07T12:25:43Z |
| spellingShingle | Data Generation for Path Testing Mansour, Nashat |
| status_str | publishedVersion |
| title | Data Generation for Path Testing |
| title_full | Data Generation for Path Testing |
| title_fullStr | Data Generation for Path Testing |
| title_full_unstemmed | Data Generation for Path Testing |
| title_short | Data Generation for Path Testing |
| title_sort | Data Generation for Path Testing |
| url | http://hdl.handle.net/10725/2967 http://dx.doi.org/10.1023/B:SQJO.0000024059.72478.4e http://link.springer.com/article/10.1023/B:SQJO.0000024059.72478.4e |