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An experimental study of hyper-heuristic selection and acceptance mechanism for combinatorial t-way test suite generation

Zamil, Kamal Z.; Din, Fakhrud; Kendall, Graham; Ahmed, Bestoun S.

Authors

Kamal Z. Zamil

Fakhrud Din

Graham Kendall Graham.Kendall@nottingham.ac.uk

Bestoun S. Ahmed



Abstract

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, metaheuristic algorithms that make up these strategies often require specific domain knowledge in order to allow effective tuning before good quality solutions can be obtained. Hyperheuristics 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.

Journal Article Type Article
Publication Date Aug 31, 2017
Journal Information Sciences
Print ISSN 0020-0255
Electronic ISSN 0020-0255
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 399
APA6 Citation Zamil, K. Z., Din, F., Kendall, G., & Ahmed, B. S. (2017). An experimental study of hyper-heuristic selection and acceptance mechanism for combinatorial t-way test suite generation. Information Sciences, 399, doi:10.1016/j.ins.2017.03.007
DOI https://doi.org/10.1016/j.ins.2017.03.007
Keywords Software testing ; t-way testing ; Hyper-heuristics ; Meta-heuristics ; Fuzzy Inference Selection
Publisher URL https://www.sciencedirect.com/science/article/pii/S0020025517305820
Copyright Statement Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0





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