An assimilated approach of concept analysis and particle swarm optimization algorithm for effective test suite minimization

In most of the test suite minimization techniques, either the size minimization is more or the fault detection is more. But a combination of both would yield better qualified reduced test suite. This paper presents a technique where the size minimization is obtained through the optimization algorithm, Particle Swarm Optimization and the Fault Detection Effectiveness is obtained through Concept Analysis. In spite of our algorithm producing results similar to Genetic Algorithm, the computation time of our algorithm is simple and improves the fault detection capacity. The experimental results indicate that PSO outperforms GAs for most code elements to be covered in terms of effectiveness and efficiency.