Nasser, Abdullah B. and Abdul-Qawy, Antar S. H. and Abdullah, Nibras and Hujainah, Fadhl and Kamal Z., Zamli and Ghanem, Waheed A. H. M. (2020) Latin hypercube sampling Jaya algorithm based strategy for T-way test suite generation. In: ACM International Conference Proceeding Series, 9th International Conference on Software and Computer Applications (ICSCA 2020) , 18 - 21 February 2020 , Langkawi. pp. 105-109.. ISBN 9781450376655
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Abstract
T-way testing is a sampling strategy that generates a subset of test cases from a pool of possible tests. Many t-way testing strategies appear in the literature to-date ranging from general computational ones to meta-heuristic based. Owing to its performance, man the meta-heuristic based t-way strategies have gained significant attention recently (e.g. Particle Swarm Optimization, Genetic Algorithm, Ant Colony Algorithm, Harmony Search, Jaya Algorithm and Cuckoo Search). Jaya Algorithm (JA) is a new metaheuristic algorithm, has been used for solving different problems. However, losing the search's diversity is a common issue in the metaheuristic algorithm. In order to enhance JA's diversity, enhanced Jaya Algorithm strategy called Latin Hypercube Sampling Jaya Algorithm (LHS-JA) for Test Suite Generation is proposed. Latin Hypercube Sampling (LHS) is a sampling approach that can be used efficiently to improve search diversity. To evaluate the efficiency of LHS-JA, LHS-JA is compared against existing metaheuristic-based t-way strategies. Experimental results have shown promising results as LHS-JA can compete with existing t-way strategies.
| Item Type: | Conference or Workshop Item (Lecture) |
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| Additional Information: | Indexed by Scopus |
| Uncontrolled Keywords: | Application of Jaya algorithm; Jaya algorithm; Metaheuristic algorithm; Optimization algorithm; T-way test suite generation |
| Subjects: | Q Science > QA Mathematics > QA76 Computer software |
| Faculty/Division: | Institute of Postgraduate Studies Faculty of Computing |
| Depositing User: | Mrs Norsaini Abdul Samat |
| Date Deposited: | 10 Nov 2021 04:52 |
| Last Modified: | 10 Nov 2021 04:52 |
| URI: | http://umpir.ump.edu.my/id/eprint/32294 |
| Download Statistic: | View Download Statistics |
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