Metaheuristic Algorithm for State-Based Software Testing
This article presents a metaheuristic algorithm for testing software, especially web applications, which can be modeled as a state transition diagram. We formulate the testing problem as an optimization problem and use a simulated annealing (SA) metaheuristic algorithm to generate test cases as sequ...
محفوظ في:
| المؤلف الرئيسي: | |
|---|---|
| مؤلفون آخرون: | , |
| التنسيق: | article |
| منشور في: |
2018
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| الوصول للمادة أونلاين: | http://hdl.handle.net/10725/10208 https://doi.org/10.1080/08839514.2018.1451222 http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://www.tandfonline.com/doi/abs/10.1080/08839514.2018.1451222 |
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إضافة وسم
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| _version_ | 1864513486193688576 |
|---|---|
| author | Haraty, Ramzi A. |
| author2 | Mansour, Nashat Zeitunlian, Hratch |
| author2_role | author author |
| author_facet | Haraty, Ramzi A. Mansour, Nashat Zeitunlian, Hratch |
| author_role | author |
| dc.creator.none.fl_str_mv | Haraty, Ramzi A. Mansour, Nashat Zeitunlian, Hratch |
| dc.date.none.fl_str_mv | 2018 2019-03-14T13:05:41Z 2019-03-14T13:05:41Z 2019-03-14 |
| dc.identifier.none.fl_str_mv | 0883-9514 http://hdl.handle.net/10725/10208 https://doi.org/10.1080/08839514.2018.1451222 Haraty, R. A., Mansour, N., & Zeitunlian, H. (2018). Metaheuristic Algorithm for State-Based Software Testing. Applied Artificial Intelligence, 32(2), 197-213. http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://www.tandfonline.com/doi/abs/10.1080/08839514.2018.1451222 |
| dc.language.none.fl_str_mv | en |
| dc.relation.none.fl_str_mv | Applied Artificial Intelligence |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.title.none.fl_str_mv | Metaheuristic Algorithm for State-Based Software Testing |
| dc.type.none.fl_str_mv | Article info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | This article presents a metaheuristic algorithm for testing software, especially web applications, which can be modeled as a state transition diagram. We formulate the 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 an energy function that is based on testing objectives such as coverage, diversity, and continuity of events. The suggested method includes a “significance weight” assigned to events, which leads to important web pages and ensures coverage of relevant features by test cases. The experimental results demonstrate the effectiveness of simulated annealing and show that SA yields good results for testing web applications in comparison with other heuristics. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | LAURepo_d330ebbf6d021cade5f43d1ef07bf5b8 |
| identifier_str_mv | 0883-9514 Haraty, R. A., Mansour, N., & Zeitunlian, H. (2018). Metaheuristic Algorithm for State-Based Software Testing. Applied Artificial Intelligence, 32(2), 197-213. |
| language_invalid_str_mv | en |
| network_acronym_str | LAURepo |
| network_name_str | Lebanese American University repository |
| oai_identifier_str | oai:laur.lau.edu.lb:10725/10208 |
| publishDate | 2018 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Metaheuristic Algorithm for State-Based Software TestingHaraty, Ramzi A.Mansour, NashatZeitunlian, HratchThis article presents a metaheuristic algorithm for testing software, especially web applications, which can be modeled as a state transition diagram. We formulate the 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 an energy function that is based on testing objectives such as coverage, diversity, and continuity of events. The suggested method includes a “significance weight” assigned to events, which leads to important web pages and ensures coverage of relevant features by test cases. The experimental results demonstrate the effectiveness of simulated annealing and show that SA yields good results for testing web applications in comparison with other heuristics.PublishedN/A2019-03-14T13:05:41Z2019-03-14T13:05:41Z20182019-03-14Articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article0883-9514http://hdl.handle.net/10725/10208https://doi.org/10.1080/08839514.2018.1451222Haraty, R. A., Mansour, N., & Zeitunlian, H. (2018). Metaheuristic Algorithm for State-Based Software Testing. Applied Artificial Intelligence, 32(2), 197-213.http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.phphttps://www.tandfonline.com/doi/abs/10.1080/08839514.2018.1451222enApplied Artificial Intelligenceinfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/102082021-03-19T10:45:22Z |
| spellingShingle | Metaheuristic Algorithm for State-Based Software Testing Haraty, Ramzi A. |
| status_str | publishedVersion |
| title | Metaheuristic Algorithm for State-Based Software Testing |
| title_full | Metaheuristic Algorithm for State-Based Software Testing |
| title_fullStr | Metaheuristic Algorithm for State-Based Software Testing |
| title_full_unstemmed | Metaheuristic Algorithm for State-Based Software Testing |
| title_short | Metaheuristic Algorithm for State-Based Software Testing |
| title_sort | Metaheuristic Algorithm for State-Based Software Testing |
| url | http://hdl.handle.net/10725/10208 https://doi.org/10.1080/08839514.2018.1451222 http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://www.tandfonline.com/doi/abs/10.1080/08839514.2018.1451222 |