基于粒子群优化的组合测试数据生成算法  

Improved algorithm for combinatorial test data generation based on particle swarm optimization

作　　者：王建峰[1] 孙超[1] 姜守达[1] 

机构地区：[1]哈尔滨工业大学电气工程与自动化学院,黑龙江哈尔滨150080

出　　处：《哈尔滨工程大学学报》2013年第4期477-482,共6页Journal of Harbin Engineering University

基　　金：航天支撑基金资助项目(2010-HT-HGD-16);中央高校基本科研业务费专项资金资助项目(HIT.NSRIF.2012014)

摘　　要：针对组合测试中测试数据的生成问题,提出了一种基于粒子群优化的组合测试数据生成算法,引入衰减阈值的概念,在每次寻优过程结束后选出适应值在衰减范围内的优秀粒子.并采用了一种有效的扰动方式,根据最优粒子情况针对部分优秀粒子进行有效扰动,在每次优化计算后能够输出多条测试数据.与传统算法相比,在保证优化程度的前提下,有效地减少优化计算的次数,提高了测试数据的生成效率.In this paper,an algorithm for test data generation,which is an important problem of combinatorial testing,based on particle swarm optimization(PSO) method was introduced.The decaying threshold mechanism was used to select all particles in the decaying range after every optimizing process.After every PSO iteration,the best particle was outputted as a test data and all these selected particles were disturbed by a new disturbance method which was based on the best data output.The results indicate that more test data can be outputted after every PSO calculation.Compared with the original algorithm,the times of optimization calculation was reduced effectively,and the efficiency of the test data generation was improved effectively on the premise of ensuring the optimization degree of the data generated.

关 键 词：组合测试 粒子群优化 测试数据生成 衰减阈值 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]