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Reseach Article

Automatic Generation of Test Suits by Applying Genetic Algorithm

Published on February 2013 by Mohd Athar, Avdhesh Gupta
International Conference on Advances in Computer Application 2013
Foundation of Computer Science USA
ICACA2013 - Number 1
February 2013
Authors: Mohd Athar, Avdhesh Gupta
c6e1dbfa-8e9e-4886-aa8c-c184ed67ff9b

Mohd Athar, Avdhesh Gupta . Automatic Generation of Test Suits by Applying Genetic Algorithm. International Conference on Advances in Computer Application 2013. ICACA2013, 1 (February 2013), 1-6.

@article{
author = { Mohd Athar, Avdhesh Gupta },
title = { Automatic Generation of Test Suits by Applying Genetic Algorithm },
journal = { International Conference on Advances in Computer Application 2013 },
issue_date = { February 2013 },
volume = { ICACA2013 },
number = { 1 },
month = { February },
year = { 2013 },
issn = 0975-8887,
pages = { 1-6 },
numpages = 6,
url = { /proceedings/icaca2013/number1/10387-1003/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Advances in Computer Application 2013
%A Mohd Athar
%A Avdhesh Gupta
%T Automatic Generation of Test Suits by Applying Genetic Algorithm
%J International Conference on Advances in Computer Application 2013
%@ 0975-8887
%V ICACA2013
%N 1
%P 1-6
%D 2013
%I International Journal of Computer Applications
Abstract

The only objective of programming is not to determine the algorithm to accomplish a result, but relevance and correctness of the result also need to be ascertained. Correctness can be insured by applying testing to the result. Testing is most critical practice which is performed for supporting quality assurance. It is substantial but also arduous to warrant the quality of software; half of the cost is consecrated to testing when we converse about software development. Efficient ways can reduce percentage of cost and time incurred in testing. In spite of scads of theoretical work in field of Software Testing, its advancement is slow towards automation. In this approach, Genetic Algorithm (GA), which is a meta-heuristic algorithm, is employed for optimizing path testing to achieve total code coverage.

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Index Terms

Computer Science
Information Sciences

Keywords

Software Testing Sut Code Coverage