Using genetic algorithms for test case generation in path testing

Authors:
Jin-Cherng Lin;Pu-Lin Yeh
Affiliations:
-;-
Venue:
ATS '00 Proceedings of the 9th Asian Test Symposium
Year:
2000

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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.