A Novel Swarm Intelligence Based Strategy to Generate Optimum Test Data in T-Way Testing

Abstract

The limitation of resources and the deadline of software and hardware projects inhibits the exhaustive testing of a system. The most effective way to overcome this problem is to generation of optimal test suite. Heuristic searches are used to optimize the test suite since 1992. Recently, the interest and activities is increasing in this area. In theory, the changes to the parameter interaction (the t) can significantly reduce the number data in the test suite. Using this principle many scientists and practitioners created some effective test suite generation strategies. The implementation of heuristic search in the generation of optimum and minimum test suite is the most effective. However, producing the optimum test data is a NP-hard problem (Non-deterministic polynomial). Thus, it is impossible for any strategy that can produce the optimum test suite in any circumstance. This paper represents a novel swarm intelligent based searching strategy (mSITG) to generate optimum test suite. The performances of the mSITG are analyzed and compared with other well-known strategies. Empirical result shows that the proposed strategy is highly acceptable in terms of the test data size.