基于改进PSO算法的测试数据自动生成研究  

Study of automatic test data generation based on improved PSO algorithm

作　　者：曹晓燕[1] 邵定宏[1] 

机构地区：[1]南京工业大学电子与信息工程学院,江苏南京211816

出　　处：《计算机工程与设计》2011年第7期2472-2475,共4页Computer Engineering and Design

摘　　要：为了提高软件测试中测试数据自动生成的效率,提出了一种基于改进PSO算法的测试数据自动生成的方法。通过在标准的PSO算法中引入人工免疫的思想,保持了群体的多样性,从而有效避免标准PSO算法易陷入局部最优的问题,提高了算法全局搜索的能力,增强了算法的整体性能。实验结果表明,利用改进后的PSO算法寻找最优解所需的迭代次数和时间明显少于标准粒子群算法,生成测试数据的速度快、效率高。In order to improve the efficiency of test data automatic generation, a method based on particle swarm optimization algorithm is proposed. By combining the particle swarm optimization algorithm with artificial immune method, the diversity of the individual is kept in the improved strategy, and it can overcome the local optimum problem of standard particle swarm optimization algorithm. The overall search capability as well as the performance of the standard algorithm is enhanced. The experimental results show that the presented algorithm obviously reduces the number of iterations and decreases the time consuming. At the same time, it can generate higher quahty and more efficiency test data.

关 键 词：改进的PSO算法 测试数据 软件测试 PSO算法 免疫算法 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]