Greedy Interaction Elements Coverage Analysis for AI-Based T-Way Strategies
Recently, many researchers have started to adopt Artificial Intelligence AI-based strategies for t-way testing.Here, each interaction is covered at most once whenever possible. In many AI-based strategies, sampling for the most optimal test cases is given utmost priority, but measuring of the inter...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Faculty of Computer Science & Information Technology, University of Malaya
2013
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/5799/1/Kamal_Z._Zamli.pdf |
| _version_ | 1825821689902006272 |
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| author | Kamal Z., Zamli Al-Sewari, Abdul Rahman Ahmed Mohammed Norazlina, Khamis |
| author_facet | Kamal Z., Zamli Al-Sewari, Abdul Rahman Ahmed Mohammed Norazlina, Khamis |
| author_sort | Kamal Z., Zamli |
| collection | UMP |
| description | Recently, many researchers have started to adopt Artificial Intelligence AI-based strategies for t-way testing.Here, each interaction is covered at most once whenever possible. In many AI-based strategies, sampling for the most optimal test cases is given utmost priority, but measuring of the interaction coverage metric per test case is often neglected. In the situation where not all test cases can be executed due to constraints on project deadline, the availability of interaction coverage metric per test case can be a useful indicator on how greedy each AI-based strategy of interests is. In this manner, test engineers can make informed decision on the selection of suitable strategies for use. In this paper, this study presents a systematic analysis of existing AIbased strategies including that of Hill Climbing HC, Simulated Annealing SA, Tabu Search TS, Great Flood GF, Particle Swarm Optimization PSTG and Harmonic Search Strategy HSS as far as its rate of coverage per test case is concerned. In doing so, this paper demonstrates that HSS, in most cases, gives competitive
interaction coverage rate as compared to competing AI-based strategies but with less number of iterations. |
| first_indexed | 2024-03-06T11:45:20Z |
| format | Article |
| id | UMPir5799 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T11:45:20Z |
| publishDate | 2013 |
| publisher | Faculty of Computer Science & Information Technology, University of Malaya |
| record_format | dspace |
| spelling | UMPir57992018-01-16T00:47:24Z http://umpir.ump.edu.my/id/eprint/5799/ Greedy Interaction Elements Coverage Analysis for AI-Based T-Way Strategies Kamal Z., Zamli Al-Sewari, Abdul Rahman Ahmed Mohammed Norazlina, Khamis QA76 Computer software Recently, many researchers have started to adopt Artificial Intelligence AI-based strategies for t-way testing.Here, each interaction is covered at most once whenever possible. In many AI-based strategies, sampling for the most optimal test cases is given utmost priority, but measuring of the interaction coverage metric per test case is often neglected. In the situation where not all test cases can be executed due to constraints on project deadline, the availability of interaction coverage metric per test case can be a useful indicator on how greedy each AI-based strategy of interests is. In this manner, test engineers can make informed decision on the selection of suitable strategies for use. In this paper, this study presents a systematic analysis of existing AIbased strategies including that of Hill Climbing HC, Simulated Annealing SA, Tabu Search TS, Great Flood GF, Particle Swarm Optimization PSTG and Harmonic Search Strategy HSS as far as its rate of coverage per test case is concerned. In doing so, this paper demonstrates that HSS, in most cases, gives competitive interaction coverage rate as compared to competing AI-based strategies but with less number of iterations. Faculty of Computer Science & Information Technology, University of Malaya 2013 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/5799/1/Kamal_Z._Zamli.pdf Kamal Z., Zamli and Al-Sewari, Abdul Rahman Ahmed Mohammed and Norazlina, Khamis (2013) Greedy Interaction Elements Coverage Analysis for AI-Based T-Way Strategies. Malaysian Journal of Computer Science, 26 (1). pp. 23-33. ISSN 0127-9084. (Published) http://mjcs.fsktm.um.edu.my/document.aspx?FileName=1344.pdf |
| spellingShingle | QA76 Computer software Kamal Z., Zamli Al-Sewari, Abdul Rahman Ahmed Mohammed Norazlina, Khamis Greedy Interaction Elements Coverage Analysis for AI-Based T-Way Strategies |
| title | Greedy Interaction Elements Coverage Analysis for AI-Based T-Way Strategies |
| title_full | Greedy Interaction Elements Coverage Analysis for AI-Based T-Way Strategies |
| title_fullStr | Greedy Interaction Elements Coverage Analysis for AI-Based T-Way Strategies |
| title_full_unstemmed | Greedy Interaction Elements Coverage Analysis for AI-Based T-Way Strategies |
| title_short | Greedy Interaction Elements Coverage Analysis for AI-Based T-Way Strategies |
| title_sort | greedy interaction elements coverage analysis for ai based t way strategies |
| topic | QA76 Computer software |
| url | http://umpir.ump.edu.my/id/eprint/5799/1/Kamal_Z._Zamli.pdf |
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