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Feasible Test Case Generation using Search based Technique

by Jasmine Minj
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 70 - Number 28
Year of Publication: 2013
Authors: Jasmine Minj
10.5120/12260-8499

Jasmine Minj . Feasible Test Case Generation using Search based Technique. International Journal of Computer Applications. 70, 28 ( May 2013), 51-54. DOI=10.5120/12260-8499

@article{ 10.5120/12260-8499,
author = { Jasmine Minj },
title = { Feasible Test Case Generation using Search based Technique },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 70 },
number = { 28 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 51-54 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume70/number28/12260-8499/ },
doi = { 10.5120/12260-8499 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:34:08.652519+05:30
%A Jasmine Minj
%T Feasible Test Case Generation using Search based Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 70
%N 28
%P 51-54
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents automatic test case generation technique. Multi population genetic algorithm is used to generate test cases. Fitness function is based on the multiple condition decision coverage criteria. MATLAB Gatool is used for implementing the test case generation algorithm. It generates efficient and effective test cases. Test cases are optimized using multi population genetic algorithm. MCDC coverage is used as coverage criteria. Automatic test cases generation reduce the testing effort, time and cost.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Multi population genetic algorithm Multiple condition decision coverage

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