DocumentCode
2752732
Title
Using genetic algorithms for test case generation in path testing
Author
Lin, Jin-Cherng ; Yeh, Pu-Lin
Author_Institution
Dept. of Comput. Sci. & Eng., Tatung Univ., Taipei, Taiwan
fYear
2000
fDate
2000
Firstpage
241
Lastpage
246
Abstract
Generic algorithms are inspired by Darwin´s survival of the fittest theory. This paper discusses a genetic algorithm that can automatically generate test cases to test a selected path. This algorithm takes a selected path as a target and executes sequences of operators iteratively for test cases to evolve. The evolved test case can lead the program execution to achieve the target path. A fitness function named SIMILARITY is defined to determine which test case should survive if the final test case has not been found
Keywords
automatic test pattern generation; genetic algorithms; logic testing; real-time systems; SIMILARITY; fitness function; genetic algorithms; operator sequences; path testing; program execution; survival of the fittest theory; test case generation; Automatic testing; Computer aided software engineering; Computer science; Genetic algorithms; Genetic engineering; Genetic mutations; Iterative algorithms; Real time systems; System testing; Time measurement;
fLanguage
English
Publisher
ieee
Conference_Titel
Test Symposium, 2000. (ATS 2000). Proceedings of the Ninth Asian
Conference_Location
Taipei
ISSN
1081-7735
Print_ISBN
0-7695-0887-1
Type
conf
DOI
10.1109/ATS.2000.893632
Filename
893632
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