An Approach to Generate Test Cases by Multi-Path Based on Genetic Algorithm

Article Preview

Abstract:

Software testing is important to ensure the quality and reliability of the software.The improvement on the automation of test case generation is the entire key to improve the automation of the testing process.It helps a lot in the generation of test cases to construct multi-path model.It is based on genetic algorithm with three parts which are the test environment construction, the genetic algorithms and the operating environment.It’s feasibility and efficiency is verified by triangle classification procedures.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

3976-3979

Citation:

Online since:

May 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Jones B F, Sthamer H H, Eyres D E. Automatic Structural Testing Genetic Algorithms[J]. Software Engineering Journal, 1996, 11 (5): 299-306.

DOI: 10.1049/sej.1996.0040

Google Scholar

[2] Michael C C, McGraw G, Schatz M A. Generating Software TestData by Evolution [J]. IEEE Transaction on Software Engineering, 2001, 27(12): 1085-1110.

DOI: 10.1109/32.988709

Google Scholar

[3] Korel B. Automated Software Data Generator [J]. IEEE Trans. On Software Eng., 1990, 16(8): 870-879.

DOI: 10.1109/32.57624

Google Scholar

[4] Pargas R P, Harrold M J. Test -data Generation Using GeneticAlgorithms [J]. The Journal of Software Testing, Verification andReliability, 1999, 9(4): 263-282.

DOI: 10.1002/(sici)1099-1689(199912)9:4<263::aid-stvr190>3.0.co;2-y

Google Scholar

[5] Berndt D, Fisher J, Johnson L. Breeding Software Test Caseswith Genetic Algorithms[C] /Proceedings of the 36th Hawaii International Conference on System Sciences, (2003).

DOI: 10.1109/hicss.2003.1174917

Google Scholar

[6] Berndt D, Fisher J, Johnson L. Comparisons of selection strategy in genetic algorithm [J], Computer Engineering and Desing 2009, 30(23).

Google Scholar