Journal of Computer Sciences and Applications
ISSN (Print): 2328-7268 ISSN (Online): 2328-725X Website: http://www.sciepub.com/journal/jcsa Editor-in-chief: Minhua Ma, Patricia Goncalves
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Journal of Computer Sciences and Applications. 2015, 3(2), 56-60
DOI: 10.12691/jcsa-3-2-7
Open AccessResearch Article

Test Data Generation Using Computational Intelligence Technique

Harsh Bhasin1, , Naresh Chauhan2 and Sandhya Pathak3

1Department of Computer Science, Jamia Hamdard, Delhi, India

2Department of Computer Science, YMCAUST, Faridabad, India

3M.Tech Scholar, CSE Department, DITMR, Faridabad, India

Pub. Date: April 24, 2015
(This article belongs to the Special Issue Applicability of Soft Computing in NP Hard Problems)

Cite this paper:
Harsh Bhasin, Naresh Chauhan and Sandhya Pathak. Test Data Generation Using Computational Intelligence Technique. Journal of Computer Sciences and Applications. 2015; 3(2):56-60. doi: 10.12691/jcsa-3-2-7

Abstract

Testing is one of the most important parts of Software Development Life Cycle. It requires the crafting of a good test. This crafting can be done only after deep analysis and knowhow of the working of the software. This work presents the Genetic Algorithm based approach for the generation of test data. The approach would automate the test data generation process and hence facilitates the process of testing. The work would also help in the elimination of human biases. The work has been implemented in C#, verified with a set of 10 moderate size software. The results are encouraging. The work is part of a larger endeavor to develop a comprehensive testing system for C #software. This work is based on a comprehensive literature review which has helped develop a sound theoretical base.

Keywords:
genetic algorithms software testing test data generation branch coverage

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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