Title :
Test case generation based on adaptive genetic algorithm
Author :
Lin, Peng ; Bao, Xiaolu ; Shu, Zhiyong ; Wang, Xiaojuan ; Liu, Jingmin
Author_Institution :
Dept. of Software Testing, China Electron. Equip. of Syst. Eng. Inst., Beijing, China
Abstract :
A novel algorithm is proposed to support test case generation of combination design in this paper. First of all, the combination-index table (CIT) is defined to guide the process of test case generation, based on which the adaptive genetic algorithm (AGA) is proposed to generate test cases. Finally, an automatic test tool for test case generation, named genetic automatic test case generation (GATG) tool, is introduced and compared with the other tools. The experiments show that the adaptive genetic algorithm performs excellent, and more controllable and convenient for test case design.
Keywords :
genetic algorithms; program testing; AGA; CIT; GATG; adaptive genetic algorithm; combination design; combination-index table; genetic automatic test case generation tool; test case design; Algorithm design and analysis; Biological cells; Genetic algorithms; Software algorithms; Software testing; Systems engineering and theory; adaptive genetic algorithm (AGA); combination-index table (CIT); t-wise strategy; test case generation;
Conference_Titel :
Quality, Reliability, Risk, Maintenance, and Safety Engineering (ICQR2MSE), 2012 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4673-0786-4
DOI :
10.1109/ICQR2MSE.2012.6246363