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Enhancement in K-mean Clustering to Analyze Software Architecture using Normalization

by Shilpa Sharma, Jyoti Godara
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 120 - Number 6
Year of Publication: 2015
Authors: Shilpa Sharma, Jyoti Godara
10.5120/21230-3973

Shilpa Sharma, Jyoti Godara . Enhancement in K-mean Clustering to Analyze Software Architecture using Normalization. International Journal of Computer Applications. 120, 6 ( June 2015), 12-15. DOI=10.5120/21230-3973

@article{ 10.5120/21230-3973,
author = { Shilpa Sharma, Jyoti Godara },
title = { Enhancement in K-mean Clustering to Analyze Software Architecture using Normalization },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 120 },
number = { 6 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 12-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume120/number6/21230-3973/ },
doi = { 10.5120/21230-3973 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:05:30.349501+05:30
%A Shilpa Sharma
%A Jyoti Godara
%T Enhancement in K-mean Clustering to Analyze Software Architecture using Normalization
%J International Journal of Computer Applications
%@ 0975-8887
%V 120
%N 6
%P 12-15
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Software engineering deals with the all kind of software production, design to coding, software accuracy and deals with the complexity of any software system. The software failing complication can be raised in the complex software's, when we are not able to properly analyze the properties of the software. In the past times the algorithm of genetic had been proposed to cluster the functions of similar properties. In the genetic algorithms, all the clustering values are depends on the chromosomes. It is very difficult to estimate the correct value of chromosomes, which decreases the efficiency of the software architecture analysis. For increasing the software architecture analysis, the K-MEAN clustering will be used which is more efficient then the genetic clustering. This will improve the software architecture analysis and improve the accuracy and reduce algorithm escape time.

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Index Terms

Computer Science
Information Sciences

Keywords

K-mean clustering Genetic algorithm centre based clustering efficiency accuracy.

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