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This paper proposes an automatic test data generation method based on Simple and Adaptive Mutation Particle Swarm Optimization algorithm. According to the particle velocity independency in the evolution, this algorithm removes particle velocity , only the position of particle control the process of evolution, avoiding problems such as slow of convergence in the late evolutionary and low-precision radiation of particle that particle velocity brings about; according to fit variance and current optimum solution, we find the current mutation rate of best particle, the operation of mutation can improve ability of global searching in the earlier evolutionary. Test examples show that it is better than basic particle swarm optimization algorithm and can improve the efficiency of automated test data generation.
Wei et al. (Tue,) studied this question.
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