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Hybrid flower pollination algorithm strategies for t-way test suite generation

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  • Abdullah B Nasser
  • Kamal Z Zamli
  • AbdulRahman A Alsewari
  • Bestoun S Ahmed

Abstract

The application of meta-heuristic algorithms for t-way testing has recently become prevalent. Consequently, many useful meta-heuristic algorithms have been developed on the basis of the implementation of t-way strategies (where t indicates the interaction strength). Mixed results have been reported in the literature to highlight the fact that no single strategy appears to be superior compared with other configurations. The hybridization of two or more algorithms can enhance the overall search capabilities, that is, by compensating the limitation of one algorithm with the strength of others. Thus, hybrid variants of the flower pollination algorithm (FPA) are proposed in the current work. Four hybrid variants of FPA are considered by combining FPA with other algorithmic components. The experimental results demonstrate that FPA hybrids overcome the problems of slow convergence in the original FPA and offers statistically superior performance compared with existing t-way strategies in terms of test suite size.

Suggested Citation

  • Abdullah B Nasser & Kamal Z Zamli & AbdulRahman A Alsewari & Bestoun S Ahmed, 2018. "Hybrid flower pollination algorithm strategies for t-way test suite generation," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-24, May.
    • Handle: RePEc:plo:pone00:0195187
    DOI: 10.1371/journal.pone.0195187
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    References listed on IDEAS

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    1. Dubey, Hari Mohan & Pandit, Manjaree & Panigrahi, B.K., 2015. "Hybrid flower pollination algorithm with time-varying fuzzy selection mechanism for wind integrated multi-objective dynamic economic dispatch," Renewable Energy, Elsevier, vol. 83(C), pages 188-202.
    2. Vitaliy Feoktistov, 2006. "Differential Evolution," Springer Optimization and Its Applications, Springer, number 978-0-387-36896-2, December.
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