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Dynamic Requirement Clustering of Requirement with Usable Test Cases by Cosine-Correlation

by Amit Verma, Chetna
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 123 - Number 11
Year of Publication: 2015
Authors: Amit Verma, Chetna
10.5120/ijca2015905594

Amit Verma, Chetna . Dynamic Requirement Clustering of Requirement with Usable Test Cases by Cosine-Correlation. International Journal of Computer Applications. 123, 11 ( August 2015), 22-24. DOI=10.5120/ijca2015905594

@article{ 10.5120/ijca2015905594,
author = { Amit Verma, Chetna },
title = { Dynamic Requirement Clustering of Requirement with Usable Test Cases by Cosine-Correlation },
journal = { International Journal of Computer Applications },
issue_date = { August 2015 },
volume = { 123 },
number = { 11 },
month = { August },
year = { 2015 },
issn = { 0975-8887 },
pages = { 22-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume123/number11/22007-2015905594/ },
doi = { 10.5120/ijca2015905594 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:13:10.838746+05:30
%A Amit Verma
%A Chetna
%T Dynamic Requirement Clustering of Requirement with Usable Test Cases by Cosine-Correlation
%J International Journal of Computer Applications
%@ 0975-8887
%V 123
%N 11
%P 22-24
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In software engineering testing plays an important role in development and maintenance of software. Component based software development gained a lot of practical importance in the field of Software engineering by the academic researcher and industry for finding reusable efficient test cases. It is the predominant problem in software engineering that clustering reduces the search space of the component of test cases by grouping of similar entities together ensuring reduce time complexity and reduce the search time for retrieve test cases according to requirement. In this research paper we investigate how k-mean work on the set of requirement and usable test cases we also define how to resolve the k-mean clustering static number of cluster when new requirement or test cases will come. In this research paper we investigate how k-mean work on the set of requirement and usable test cases we also define how to resolve the k-mean clustering static number of cluster when new requirement or test cases will come. Here we purposed an approach for dynamic clustering for test cases and requirement.

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Index Terms

Computer Science
Information Sciences

Keywords

Clustering correlation retrieval K-mean

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