Cost-effective test case generation with the hyper-heuristic for software product line testing
Implementation of optimization algorithm for test case generation in Model-Based Testing (MBT) for Software Product Line (SPL) has been increasing, due to the demand for optimal test case results with a balanced trade-off between cost and effectiveness measure. This paper proposed a hyper-heuristic...
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my.utm.1048812024-03-25T09:15:54Z http://eprints.utm.my/104881/ Cost-effective test case generation with the hyper-heuristic for software product line testing Sulaiman, Rabatul Aduni Jawawi, Dayang N. A. Abdul Halim, Shahliza QA76 Computer software Implementation of optimization algorithm for test case generation in Model-Based Testing (MBT) for Software Product Line (SPL) has been increasing, due to the demand for optimal test case results with a balanced trade-off between cost and effectiveness measure. This paper proposed a hyper-heuristic test cases generation approach in MBT for SPL called Improvement Selection Rules-Modified Choice Function (ISR-MCF). ISR-MCF is implemented with three search operators which are Non-Dominated Sorting Genetic Algorithm II with low-level heuristic (NSGA-II-LLH), Strength Pareto Evolutionary with Low-Level Heuristic (SPEA 2-LLH) and Particle Swarm Optimization with Low-Level Heuristic (PSO-LLH). The approach was evaluated with a test model and the result shows that the proposed ISR-MCF with NSGA-II-LLH outperforms other existing rules for minimization measure (size of a test suite and execution time and maximization measure (coverage criteria). Elsevier Ltd 2023 Article PeerReviewed Sulaiman, Rabatul Aduni and Jawawi, Dayang N. A. and Abdul Halim, Shahliza (2023) Cost-effective test case generation with the hyper-heuristic for software product line testing. Advances in Engineering Software, 175 (NA). NA-NA. ISSN 0965-9978 http://dx.doi.org/10.1016/j.advengsoft.2022.103335 DOI : 10.1016/j.advengsoft.2022.103335 |
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QA76 Computer software Sulaiman, Rabatul Aduni Jawawi, Dayang N. A. Abdul Halim, Shahliza Cost-effective test case generation with the hyper-heuristic for software product line testing |
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Implementation of optimization algorithm for test case generation in Model-Based Testing (MBT) for Software Product Line (SPL) has been increasing, due to the demand for optimal test case results with a balanced trade-off between cost and effectiveness measure. This paper proposed a hyper-heuristic test cases generation approach in MBT for SPL called Improvement Selection Rules-Modified Choice Function (ISR-MCF). ISR-MCF is implemented with three search operators which are Non-Dominated Sorting Genetic Algorithm II with low-level heuristic (NSGA-II-LLH), Strength Pareto Evolutionary with Low-Level Heuristic (SPEA 2-LLH) and Particle Swarm Optimization with Low-Level Heuristic (PSO-LLH). The approach was evaluated with a test model and the result shows that the proposed ISR-MCF with NSGA-II-LLH outperforms other existing rules for minimization measure (size of a test suite and execution time and maximization measure (coverage criteria). |
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Sulaiman, Rabatul Aduni Jawawi, Dayang N. A. Abdul Halim, Shahliza |
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Sulaiman, Rabatul Aduni Jawawi, Dayang N. A. Abdul Halim, Shahliza |
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Sulaiman, Rabatul Aduni |
title |
Cost-effective test case generation with the hyper-heuristic for software product line testing |
title_short |
Cost-effective test case generation with the hyper-heuristic for software product line testing |
title_full |
Cost-effective test case generation with the hyper-heuristic for software product line testing |
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Cost-effective test case generation with the hyper-heuristic for software product line testing |
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Cost-effective test case generation with the hyper-heuristic for software product line testing |
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cost-effective test case generation with the hyper-heuristic for software product line testing |
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Elsevier Ltd |
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2023 |
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http://eprints.utm.my/104881/ http://dx.doi.org/10.1016/j.advengsoft.2022.103335 |
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