A Comparative Study of the Effectiveness of Meta-Heuristic Techniques in Pairwise Testing

In this paper, three meta-heuristic techniques are studied and their results are compared for pairwise testing by generating the test cases. The aim of this paper is to minimize the number of test cases that are needed to be checked for pairwise testing. The techniques studied are Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Elephant Herding Optimization (EHO). The test cases thus generated check the software for each pair of input parameters. The results generated using pairwise testing show that PSO and EHO perform slightly better than GA for most of the input configurations.

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