Combinatorial Test Suites Generation Method Based on Fuzzy Genetic Algorithm

In this paper, we present an algorithm for generating combinatorial test suites using Fuzzy Genetic Algorithm (FGA). According to the problem of falling into local optimum of the traditional Genetic Algorithm (GA) method, we introduce the fuzzy control method to select the cross and variation probability adaptively using the entropy and discrete degree in the population, which improves the efficiency and reduces the time of generating the test data. Compared to other well-known algorithms, the final experiment results show the competitiveness of our algorithm both in the test suite size and the running time.

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