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Profiling of Test Cases with Clustering Methodology

by Fayaz Ahmad Khan, Anil Kumar Gupta, Dibya Jyoti Bora
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 106 - Number 14
Year of Publication: 2014
Authors: Fayaz Ahmad Khan, Anil Kumar Gupta, Dibya Jyoti Bora
10.5120/18591-9914

Fayaz Ahmad Khan, Anil Kumar Gupta, Dibya Jyoti Bora . Profiling of Test Cases with Clustering Methodology. International Journal of Computer Applications. 106, 14 ( November 2014), 32-37. DOI=10.5120/18591-9914

@article{ 10.5120/18591-9914,
author = { Fayaz Ahmad Khan, Anil Kumar Gupta, Dibya Jyoti Bora },
title = { Profiling of Test Cases with Clustering Methodology },
journal = { International Journal of Computer Applications },
issue_date = { November 2014 },
volume = { 106 },
number = { 14 },
month = { November },
year = { 2014 },
issn = { 0975-8887 },
pages = { 32-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume106/number14/18591-9914/ },
doi = { 10.5120/18591-9914 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:39:25.355270+05:30
%A Fayaz Ahmad Khan
%A Anil Kumar Gupta
%A Dibya Jyoti Bora
%T Profiling of Test Cases with Clustering Methodology
%J International Journal of Computer Applications
%@ 0975-8887
%V 106
%N 14
%P 32-37
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Software testing is an imperative task in software development process. Software testing is used to identify the correctness, completeness and quality of the software product or system. Till date, software testing is considered as a very expensive activity as it takes a lot of testing efforts, time and cost to perform it. One of the expansive factors behind is the design or generation of effective test cases for a particular software product. In this paper, we are trying to find out the effective test cases from the generated whole set on the basis of clustering methodology so that the size of test suit is reduced and redundant test cases are eliminated automatically. Here, we are following the famous K-Means algorithm with a proper distance measure.

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Index Terms

Computer Science
Information Sciences

Keywords

Software Engineering Software Testing Test Cases Clustering K-Means

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