关键词: 软件测试, 测试数据生成, 简化的自适应变异, 粒子群算法

Abstract: An improved Simple and Adaptive Mutation Particle Swarm Optimization（SAMPSO） algorithm is proposed here based on the combination of simple particle swarm optimization and adaptive mutation particle swarm optimization for automated software test data generation.During the run time，the mutation probability for the current best particle is determined by two factors：the variance of the population fitness and the current optimal solution.The mutation operator is designed to enhance the global search capability of PSO algorithm at starting.The particle velocity is discarded.The evolutionary process is only controlled by the variables of the particle position.Test examples show that it is better than basic particle swarm optimization algorithm and can improve the efficiency of automated test data generation.

Key words: software testing, test data generation, simple and adaptive mutation, Particle Swarm Optimization（PSO）