An Experimental Study of Hyper-heuristic Selection and Acceptance Mechanism for Combinatorial T-Way Test Suite Generation
Recently, many meta-heuristic algorithms have been proposed to serve as the basis of a t-way test generation strategy (where t indicates the interaction strength) including Genetic Algorithms (GA), Ant Colony Optimization (ACO), Simulated Annealing (SA), Cuckoo Search (CS), Particle Swarm Optimizati...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier Ltd
2017
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| Online Access: | http://umpir.ump.edu.my/id/eprint/14604/2/An%20experimental%20study%20of%20hyper-heuristic%20selection%20and%20acceptance%20mechanism%20for%20combinatorial%20t-way%20test%20suite%20generation%201.pdf |
| _version_ | 1825823197344301056 |
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| author | Kamal Z., Zamli Fakhrud, Din Kendall, Graham Ahmed, Bestoun S. |
| author_facet | Kamal Z., Zamli Fakhrud, Din Kendall, Graham Ahmed, Bestoun S. |
| author_sort | Kamal Z., Zamli |
| collection | UMP |
| description | Recently, many meta-heuristic algorithms have been proposed to serve as the basis of a t-way test generation strategy (where t indicates the interaction strength) including Genetic Algorithms (GA), Ant Colony Optimization (ACO), Simulated Annealing (SA), Cuckoo Search (CS), Particle Swarm Optimization (PSO), and Harmony Search (HS). Although useful, meta-heuristic algorithms that make up these strategies often require specific domain knowledge in order to allow effective tuning before good quality solutions can be obtained. Hyper-heuristics provide an alternative methodology to meta-heuristics which permit adaptive selection and/or generation of meta-heuristics automatically during the search process. This paper describes our experience with four hyper-heuristic selection and acceptance mechanisms namely Exponential Monte Carlo with counter (EMCQ), Choice Function (CF), Improvement Selection Rules (ISR), and newly developed Fuzzy Inference Selection (FIS), using the t-way test generation problem as a case study. Based on the experimental results, we offer insights on why each strategy differs in terms of its performance. |
| first_indexed | 2024-03-06T12:07:49Z |
| format | Article |
| id | UMPir14604 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T12:07:49Z |
| publishDate | 2017 |
| publisher | Elsevier Ltd |
| record_format | dspace |
| spelling | UMPir146042018-01-15T07:00:35Z http://umpir.ump.edu.my/id/eprint/14604/ An Experimental Study of Hyper-heuristic Selection and Acceptance Mechanism for Combinatorial T-Way Test Suite Generation Kamal Z., Zamli Fakhrud, Din Kendall, Graham Ahmed, Bestoun S. QA76 Computer software Recently, many meta-heuristic algorithms have been proposed to serve as the basis of a t-way test generation strategy (where t indicates the interaction strength) including Genetic Algorithms (GA), Ant Colony Optimization (ACO), Simulated Annealing (SA), Cuckoo Search (CS), Particle Swarm Optimization (PSO), and Harmony Search (HS). Although useful, meta-heuristic algorithms that make up these strategies often require specific domain knowledge in order to allow effective tuning before good quality solutions can be obtained. Hyper-heuristics provide an alternative methodology to meta-heuristics which permit adaptive selection and/or generation of meta-heuristics automatically during the search process. This paper describes our experience with four hyper-heuristic selection and acceptance mechanisms namely Exponential Monte Carlo with counter (EMCQ), Choice Function (CF), Improvement Selection Rules (ISR), and newly developed Fuzzy Inference Selection (FIS), using the t-way test generation problem as a case study. Based on the experimental results, we offer insights on why each strategy differs in terms of its performance. Elsevier Ltd 2017 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/14604/2/An%20experimental%20study%20of%20hyper-heuristic%20selection%20and%20acceptance%20mechanism%20for%20combinatorial%20t-way%20test%20suite%20generation%201.pdf Kamal Z., Zamli and Fakhrud, Din and Kendall, Graham and Ahmed, Bestoun S. (2017) An Experimental Study of Hyper-heuristic Selection and Acceptance Mechanism for Combinatorial T-Way Test Suite Generation. Information Sciences, 399. pp. 121-153. ISSN 0020-0255. (Published) http://doi.org/10.1016/j.ins.2017.03.007 DOI: 10.1016/j.ins.2017.03.007 |
| spellingShingle | QA76 Computer software Kamal Z., Zamli Fakhrud, Din Kendall, Graham Ahmed, Bestoun S. An Experimental Study of Hyper-heuristic Selection and Acceptance Mechanism for Combinatorial T-Way Test Suite Generation |
| title | An Experimental Study of Hyper-heuristic Selection and Acceptance Mechanism for Combinatorial T-Way Test Suite Generation |
| title_full | An Experimental Study of Hyper-heuristic Selection and Acceptance Mechanism for Combinatorial T-Way Test Suite Generation |
| title_fullStr | An Experimental Study of Hyper-heuristic Selection and Acceptance Mechanism for Combinatorial T-Way Test Suite Generation |
| title_full_unstemmed | An Experimental Study of Hyper-heuristic Selection and Acceptance Mechanism for Combinatorial T-Way Test Suite Generation |
| title_short | An Experimental Study of Hyper-heuristic Selection and Acceptance Mechanism for Combinatorial T-Way Test Suite Generation |
| title_sort | experimental study of hyper heuristic selection and acceptance mechanism for combinatorial t way test suite generation |
| topic | QA76 Computer software |
| url | http://umpir.ump.edu.my/id/eprint/14604/2/An%20experimental%20study%20of%20hyper-heuristic%20selection%20and%20acceptance%20mechanism%20for%20combinatorial%20t-way%20test%20suite%20generation%201.pdf |
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