A Memetic Algorithm for test data generation of object-oriented software

被引:13
作者
Arcuri, Andrea [1 ]
Yao, Xin [1 ]
机构
[1] Univ Birmingham, Sch Comp Sci, CERCIA, Birmingham B15 2TT, W Midlands, England
来源
2007 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-10, PROCEEDINGS | 2007年
关键词
D O I
10.1109/CEC.2007.4424725
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Generating test data for Object-Oriented (00) software is a hard task. Little work has been done on the subject, and a lot of open problems still need to be investigated. In this paper we focus on container classes. They are used in almost every type of software, hence their reliability is of utmost importance. We present novel techniques to generate test data for container classes in an automatic way. A new representation with novel search operators is described and tested. A way to reduce the search space for 00 software is presented. This is achieved by dynamically eliminating the functions that cannot give any further help from the search. Besides, the problem of applying the branch distances of disjunctions and conjunctions to 00 software is solved. Finally, Hill Climbing, Genetic Algorithms and Memetic Algorithms are used and compared. Our empirical case study shows that our Memetic Algorithm outperforms the other algorithms.
引用
收藏
页码:2048 / 2055
页数:8
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