Utilization of Gravitational Search Algorithm for Combinatorial T-Way Testing

Abstract

Different techniques of software testing are adopted to deal with bugs found in the highly complicated multifunctional software. However, those techniques have difficulty detecting bugs effectively because most of the bugs are triggered by interaction failures between the input parameters and values in the system. Thus, combinatorial t-way testing strategies have come into existence to produce quality minimized test cases, as well as those test cases can cover all the necessary interactions of parameters once at the least. Besides, as t-way testing is considered as an NP-hard problem, new strategies are always welcomed in this research area in pursuit of the optimum test suite. The main point of this paper is to propose the concept of a type of artificial intelligence (AI) algorithm called gravitational search algorithm (GSA) for t-way interaction testing. GSA is a stochastic optimization algorithm inspired by Newton’s law of gravity and motion and has been widely applied to figure out optimal solutions to real-world issues.