Abstract
Real World is filled with various hard and complex problems. One such complex problem is an optimization problem. Optimization has been an active area of research for several decades. Optimized solutions are hard to find so there are no deterministic algorithms that can find exact solution in polynomial time. In large domain of applications of intelligence techniques we are interested in exploring the application of Biographical Based Optimization (BBO) and Grey Wolf Optimizer (GWO) meta-heuristic algorithm to the domain of software testing. The GWO mimics the leadership hierarchy and hunting mechanism of grey wolves in nature. In this paper we adapt BBO and GWO for test suite prioritization and minimization and evaluate their performance with other nature inspired meta-heuristics.
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Gupta, D., Gupta, V. (2017). Test Suite Prioritization Using Nature Inspired Meta-Heuristic Algorithms. In: Madureira, A., Abraham, A., Gamboa, D., Novais, P. (eds) Intelligent Systems Design and Applications. ISDA 2016. Advances in Intelligent Systems and Computing, vol 557. Springer, Cham. https://doi.org/10.1007/978-3-319-53480-0_22
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DOI: https://doi.org/10.1007/978-3-319-53480-0_22
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