Optimization metaheuristic for software testing
This paper presents an evolutionary method for testing web applications. Although state-based testing has been reported, few papers have addressed modern web applications. In our work, we model web applications by associating features or web pages with states; state transition diagrams are based on...
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| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , |
| التنسيق: | conferenceObject |
| منشور في: |
2013
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://hdl.handle.net/10725/7816 https://doi.org/10.1007/978-3-642-31519-0_30 http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://link.springer.com/chapter/10.1007%2F978-3-642-31519-0_30 |
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إضافة وسم
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| _version_ | 1864513467060322305 |
|---|---|
| author | Mansour, Nashat |
| author2 | Zeitunlian, Hratch Tarhini, Abbas |
| author2_role | author author |
| author_facet | Mansour, Nashat Zeitunlian, Hratch Tarhini, Abbas |
| author_role | author |
| dc.creator.none.fl_str_mv | Mansour, Nashat Zeitunlian, Hratch Tarhini, Abbas |
| dc.date.none.fl_str_mv | 2013 2018-05-16T06:07:29Z 2018-05-16T06:07:29Z 2018-05-16 |
| dc.identifier.none.fl_str_mv | 9783642315190 http://hdl.handle.net/10725/7816 https://doi.org/10.1007/978-3-642-31519-0_30 Mansour, N., Zeitunlian, H., & Tarhini, A. (2013). Optimization metaheuristic for software testing. In EVOLVE-A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation II (pp. 463-474). Springer Berlin Heidelberg. http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://link.springer.com/chapter/10.1007%2F978-3-642-31519-0_30 |
| dc.language.none.fl_str_mv | en |
| dc.publisher.none.fl_str_mv | Springer |
| dc.relation.none.fl_str_mv | Advances in intelligent systems and computing 175 |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Evolutionary computation -- Congresses Genetic programming (Computer science) -- Congresses Combinatorial optimization -- Congresses |
| dc.title.none.fl_str_mv | Optimization metaheuristic for software testing |
| dc.type.none.fl_str_mv | Conference Paper / Proceeding info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/conferenceObject |
| description | This paper presents an evolutionary method for testing web applications. Although state-based testing has been reported, few papers have addressed modern web applications. In our work, we model web applications by associating features or web pages with states; state transition diagrams are based on events representing state transitions. We formulate the web application testing problem as an optimization problem and use a simulated annealing (SA) metaheuristic algorithm to generate test cases as sequences of events while keeping the test suite size reasonable. SA evolves a solution by minimizing a function that is based on the contradictory objectives of coverage of events, diversity of events covered, and definite continuity of events. Our experimental results show that the proposed simultaneous-operation SA gives better results than an incremental SA version and significantly better than a greedy algorithm. |
| eu_rights_str_mv | openAccess |
| format | conferenceObject |
| id | LAURepo_ce6e158d58305a3d07ba7800f7aa37c6 |
| identifier_str_mv | 9783642315190 Mansour, N., Zeitunlian, H., & Tarhini, A. (2013). Optimization metaheuristic for software testing. In EVOLVE-A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation II (pp. 463-474). Springer Berlin Heidelberg. |
| language_invalid_str_mv | en |
| network_acronym_str | LAURepo |
| network_name_str | Lebanese American University repository |
| oai_identifier_str | oai:laur.lau.edu.lb:10725/7816 |
| publishDate | 2013 |
| publisher.none.fl_str_mv | Springer |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Optimization metaheuristic for software testingMansour, NashatZeitunlian, HratchTarhini, AbbasEvolutionary computation -- CongressesGenetic programming (Computer science) -- CongressesCombinatorial optimization -- CongressesThis paper presents an evolutionary method for testing web applications. Although state-based testing has been reported, few papers have addressed modern web applications. In our work, we model web applications by associating features or web pages with states; state transition diagrams are based on events representing state transitions. We formulate the web application testing problem as an optimization problem and use a simulated annealing (SA) metaheuristic algorithm to generate test cases as sequences of events while keeping the test suite size reasonable. SA evolves a solution by minimizing a function that is based on the contradictory objectives of coverage of events, diversity of events covered, and definite continuity of events. Our experimental results show that the proposed simultaneous-operation SA gives better results than an incremental SA version and significantly better than a greedy algorithm.N/Axxiii, 506 pages : illustrations.Includes bibliographical references.Springer2018-05-16T06:07:29Z2018-05-16T06:07:29Z20132018-05-16Conference Paper / Proceedinginfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject9783642315190http://hdl.handle.net/10725/7816https://doi.org/10.1007/978-3-642-31519-0_30Mansour, N., Zeitunlian, H., & Tarhini, A. (2013). Optimization metaheuristic for software testing. In EVOLVE-A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation II (pp. 463-474). Springer Berlin Heidelberg.http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.phphttps://link.springer.com/chapter/10.1007%2F978-3-642-31519-0_30enAdvances in intelligent systems and computing175info:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/78162023-06-08T08:33:35Z |
| spellingShingle | Optimization metaheuristic for software testing Mansour, Nashat Evolutionary computation -- Congresses Genetic programming (Computer science) -- Congresses Combinatorial optimization -- Congresses |
| status_str | publishedVersion |
| title | Optimization metaheuristic for software testing |
| title_full | Optimization metaheuristic for software testing |
| title_fullStr | Optimization metaheuristic for software testing |
| title_full_unstemmed | Optimization metaheuristic for software testing |
| title_short | Optimization metaheuristic for software testing |
| title_sort | Optimization metaheuristic for software testing |
| topic | Evolutionary computation -- Congresses Genetic programming (Computer science) -- Congresses Combinatorial optimization -- Congresses |
| url | http://hdl.handle.net/10725/7816 https://doi.org/10.1007/978-3-642-31519-0_30 http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://link.springer.com/chapter/10.1007%2F978-3-642-31519-0_30 |