T-Way Strategy for Sequence Input Interaction Test Case Generation Adopting Fish Swarm Algorithm

Abstract

In Combinatorial Input Interaction (CII) based system, the increasing number of input event causes the increasing number of test cases. Since twenty years many useful T-way strategies have been developed to reduce test case size. In order to reduce test cases several T-way sequence input interaction strategies are explored, such as, Bee Algorithm(BA), Kuhn encoding (K), ASP with Clasp, CP with Sugar, Erdem (ER) exact encoding, Tarui (TA) Method, U, UR, D and DR, Brain (BR). However, none of them claim that for all test configuration the produced test cases are best. The reason is that the T-way sequence input interaction is NP-Hard problem. In this research, Fish Swarm algorithm is proposed to adapt with T-way sequence input interaction test strategy. The proposed system is compared with the other renowned search-based T-way strategies. The result shows that the proposed system is able to generate feasible and optimal results.