基于GA-PSO算法的路径测试数据自动生成*

为了实现测试数据自动生成，许多遗传算法及其改进算法应用到了测试领域。针对遗传算法具有较强的全局搜索能力，但局部搜索能力较弱，且收敛速度慢的特点。将遗传算法与粒子群算法结合起来形成新的混合算法（GA-PSO），并成功应用到软件测试数据自动生成过程中。实验结果表明，该算法结合了遗传算法和粒子群算法的优点，在保证软件测试数据正确生成的情况下，极大地提高了数据生成的效率。

Automatic generation of path test data based on GA-PSO

In order to achieve test data automatic generation, much genetic algorithm or improved algorithm had been brought into test field. According to the characteristics of strong global search, but weak local search and slow convergence of genetic algorithm, this paper proposed a new hybrid algorithm (GA-PSO) which combined GA and PSO, and applied it successfully to automatic software test data generation. The experimental results show that the new algorithm has combined the advantages of genetic algorithm and particle swarm optimization, and it has greatly enhanced the efficiency of data generation in ensuring the generation of correct test data.