DocumentCode
2691641
Title
A Memetic Algorithm for test data generation of Object-Oriented software
Author
Arcuri, Andrea ; Yao, Xin
Author_Institution
Univ. of Birmingham, Birmingham
fYear
2007
fDate
25-28 Sept. 2007
Firstpage
2048
Lastpage
2055
Abstract
Generating test data for object-oriented (OO) 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 OO 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 OO 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.
Keywords
Java; genetic algorithms; object-oriented programming; program testing; software reliability; branch distance; conjunctions; container class; disjunctions; genetic algorithm; hill climbing; memetic algorithm; object-oriented software; search operators; software reliability; test data generation; Automatic testing; Computer bugs; Containers; Genetic algorithms; Software algorithms; Software engineering; Software testing; System testing; Tree data structures; Writing;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2007. CEC 2007. IEEE Congress on
Conference_Location
Singapore
Print_ISBN
978-1-4244-1339-3
Electronic_ISBN
978-1-4244-1340-9
Type
conf
DOI
10.1109/CEC.2007.4424725
Filename
4424725
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