HABCSm: A Hamming Based t-way Strategy based on Hybrid Artificial Bee Colony for Variable Strength Test Sets Generation
Keywords:
Software testing, Combinatorial testing, t-way testing, Variable strength interaction, an optimization problem, Hybrid artificial bee colony algorithmAbstract
Search-based software engineering that involves the deployment of meta-heuristics in applicable software processes has been gaining wide attention. Recently, researchers have been advocating the adoption of meta-heuristic algorithms for t-way testing strategies (where t points the interaction strength among parameters). Although helpful, no single meta-heuristic based t-way strategy can claim dominance over its counterparts. For this reason, the hybridization of meta-heuristic algorithms can help to ascertain the search capabilities of each by compensating for the limitations of one algorithm with the strength of others. Consequently, a new meta-heuristic based t-way strategy called Hybrid Artificial Bee Colony (HABCSm) strategy, based on merging the advantages of the Artificial Bee Colony (ABC) algorithm with the advantages of a Particle Swarm Optimization (PSO) algorithm is proposed in this paper. HABCSm is the first t-way strategy to adopt Hybrid Artificial Bee Colony (HABC) algorithm with Hamming distance as its core method for generating a final test set and the first to adopt the Hamming distance as the final selection criterion for enhancing the exploration of new solutions. The experimental results demonstrate that HABCSm provides superior competitive performance over its counterparts. Therefore, this finding contributes to the field of software testing by minimizing the number of test cases required for test execution.
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[22] Gergin, Z.; Nükhet T.; Sakir E. (2019). Clustering approach using artificial bee colony algorithm for healthcare waste disposal facility location problem, International Journal of Operations Research and Information Systems (IJORIS), 10 (1), 56-75, 2019. https://doi.org/10.4018/IJORIS.2019010104
[23] Xie, F.; Li, F.; Lei, C.; Yang, J.; Zhang, Y. (2019). Unsupervised band selection based on artificial bee colony algorithm for hyperspectral image classification, Applied Soft Computing, 75, 428-440, 2019. https://doi.org/10.1016/j.asoc.2018.11.014
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[26] Kefayat, M.; Ara, L.; Niaki, S.N. (2015). A hybrid of ant colony optimization and artificial bee colony algorithm for probabilistic optimal placement and sizing of distributed energy resources, Energy Conversion and Management, 92, 149-161, 2015. https://doi.org/10.1016/j.enconman.2014.12.037
[27] Cohen, M.B.; Colbourn, C.J.; Ling, A.H. (2008). Constructing strength three covering arrays with augmented annealing, Discrete Mathematics, 308 (13), 2709-2722, 2008. https://doi.org/10.1016/j.disc.2006.06.036
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[29] Hedayat, A.S.; Sloane, N.J.A.; Stufken, J. (2012). Orthogonal arrays: theory and applications, Springer Science & Business Media, 2012.
[30] Nie, C.; Leung, H. (2011). A survey of combinatorial testing, ACM Computing Surveys (CSUR), 43 (2), 1-29, 2011. https://doi.org/10.1145/1883612.1883618
[31] Cohen, M.B.; Gibbons, P.B.; Mugridge, W.B.; Colbourn, C.J.; Collofello, J.S. (2003). A variable strength interaction testing of components, Proceedings 27th Annual International Computer Software and Applications Conference, 413-418, 2003.
[32] Homaid, A.B.; Alsewari, A.; Zamli, K.; Alsariera, Y.A. (2019). Adapting the elitism on greedy algorithm for variable strength combinatorial test cases generation, IET Software, 13 (4), 286-294, 2019. https://doi.org/10.1049/iet-sen.2018.5005
[33] Bush, K.A. (1952). Orthogonal arrays of index unity, The Annals of Mathematical Statistics, 426-434, 1952. https://doi.org/10.1214/aoms/1177729387
[34] Williams, A.W. (2000). Determination of test configurations for pair-wise interaction coverage, Testing of Communicating Systems, 59-74, 2000. https://doi.org/10.1007/978-0-387-35516-0_4
[35] Lei, Y.; Tai, K.C. (1998). In-parameter-order: A test generation strategy for pairwise testing, Proceedings Third IEEE International High-Assurance Systems Engineering Symposium (Cat. No. 98EX231), 254-261, 1998.
[36] Forbes, M.; Lawrence, J.; Lei, Y.; Kacker, R.N; Kuhn, D.R. (2008). Refining the in-parameterorder strategy for constructing covering arrays, Journal of Research of the National Institute of Standards and Technology, 113 (5), 287, 2008. https://doi.org/10.6028/jres.113.022
[37] Lei, Y.; Kacker, R.; Kuhn, D.R.; Okun, V.; Lawrence, J. (2008). IPOG/IPOG-D: efficient test generation for multi-way combinatorial testing, Software Testing, Verification and Reliability, 18 (3), 125-148, 2008. https://doi.org/10.1002/stvr.381
[38] Lei, Y.; Kacker, R.; Kuhn, D.R.; Okun, V.; Lawrence, J. (2007). IPOG: A general strategy for t-way software testing, 14th Annual IEEE International Conference and Workshops on the Engineering of Computer-Based Systems (ECBS'07), 549-556, 2007. https://doi.org/10.1109/ECBS.2007.47
[39] Cohen, D.M.; Dalal, S.R.; Fredman, M.L.; Patton, G.C. (1997). The AETG system: An approach to testing based on combinatorial design, IEEE Transactions on Software Engineering, 23 (7), 437-444, 1997. https://doi.org/10.1109/32.605761
[40] Jenkins, "Jenny". Available: http://www.burtleburtle.net/bob/math/, Accesed on 2003.
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