GAPSO: Optimal test set generator for pairwise testing

Abstract

Exhaustive testing is impossible for all sorts of software systems, owing to the cost and time consumption. Combinatorial testing is the solution to this issue and aims at picking the necessary set of parameters which can ensure high degree of interaction between the parameters. This paper presents a new approach for generating unique test cases by exploiting Genetic and Particle Swarm Optimization (GAPSO) algorithm for achieving pairwise testing. The generated test cases are refined, so as to arrive at the optimal test set. The outcome of the proposed algorithm is the minimal count of high quality test cases.