摘要
软件测试是一种极为有效的软件质量保证手段。测试数据生成是软件测试的关键。基于智能优化算法的测试数据生成方法为自动化的测试数据生成提供了解决问题的一个有效手段。首先重点总结归纳了在基于智能优化算法的测试数据生成中使用最为频繁的两种算法:遗传算法和粒子群优化算法的研究成果,分析了研究现状,接着简单介绍了基于智能优化算法的测试数据生成工具:AUSTIN和Evo Suite,最后对存在的问题及未来的研究内容进行了尝试性的探讨。
Software testing is a very effective means of quality assurance and test data generation plays a key role in it.Test data generation based on intelligent optimization algorithm provides an effective solution to the problem of automated test data generation. And genetic algorithm and particle swarm optimization algorithm are the two most frequently used optimization algorithms in these methods based on intelligent optimization algorithm. Firstly, the current research results are summed up and the research status quo is analyzed in particular. Secondly, test data generation tools：AUSTIN and Evo Suite are introduced simply. Finally, the existing problems and future researches are discussed tentatively.
作者
薛猛
姜淑娟
王荣存
XUE Meng;JIANG Shujuan;WANG Rongcun(Mine Digitization Engineering Research Center of the Ministry of Education,School of Computer Science and Technology,China University of Mining and Technology,Xuzhou,Jiangsu 221116,China)
出处
《计算机工程与应用》
CSCD
北大核心
2018年第17期16-23,共8页
Computer Engineering and Applications
基金
国家自然科学基金(No.61673384
No.61502497)
中国博士后科学基金(No.2015M581887)
徐州市科技计划项目(No.KC15SM051)
关键词
软件测试
测试数据生成
智能优化算法
遗传算法
粒子群优化
software testing
test data generation
intelligent optimization algorithm
Genetic Algorithm（GA）
ParticleSwarm Optimization（PSO）
