A uniform strength t-way test suite generator based on ant colony optimization algorithm to produce minimum test suite size

T-way testing can be used to effectively detect faults due to interactions of input parameters, which is difficult to find by other testing techniques. This testing technique able to solve exhaustive testing issue that is impossible to be implemented due to time and cost limitations. Uniform strength t-way testing works by interacting input parameter values uniformly. Pairwise testing (i.e. strength, t = 2) is a well-known types of t-way testing. However, there is a need for strength value to be greater than two. Besides, more faults can be detected by interaction greater than six. Thus, this paper focuses on developing a T-way Test Suite Generator based on Ant Colony algorithm (TTSGA) strategy that supports uniform strength. TTSGA strategy is a metaheuristic based strategy and adopts Ant Colony algorithm. Seven experiments have been performed to see its performance to produce minimum test suite size. Two non-parametric tests, which are Wilcoxon Rank and Friedman test, have been conducted to analyze the results statistically. TTSGA shows competitive results especially for higher strength (i.e. t > 3) and ranked third based on Friedman test.