Using the Particle Swarm Optimization Algorithm to Generate the Minimum Test Suite in Covering Array with Uniform Strength

Up to now, several useful algorithms have been proposed to generate covering array, which is one of the branches of combinatorial testing. The main challenge in generating such arrays is generation of the arrays with a minimum number of test cases (for efficiency) at a proper time (for performance), for large systems. Covering array generation strategies are often divided into two general categories: computational and meta-heuristic. Computational strategies usually benefit high performance but have poor results in terms of efficiency. On the other hand, meta-heuristic strategies enjoy good efficiency but suffer low performance. Among the available strategies, the DPSO strategy generates the best results in terms of efficiency, but it does not benefit high performance; in contrast the GS strategy benefits good performance but has not good efficiency. Generally, there is no strategy that is good in terms of both efficiency and performance. In this paper, we try to produce an appropriate test suite of high efficiency and performance using PSO. A simple and effective minimizer function has also been used to increase the efficiency. The evaluation results show that the proposed solution has desirable outcomes in terms of efficiency and performance.