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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| Format: | conferenceObject |
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2013
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| Online Access: | 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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| Summary: | 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. |
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