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Validation of Software Quality Models using Machine Learning: An Empirical Study

Published on November 2013 by Surbhi Gaur, Savleen Kaur, Inderpreet Kaur
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8th National Conference on Next generation Computing Technologies and Applications
Foundation of Computer Science USA
NGCTA - Number 1
November 2013
Authors: Surbhi Gaur, Savleen Kaur, Inderpreet Kaur
25f216a8-638e-4c5b-a0d5-0c82c209ccd0

Surbhi Gaur, Savleen Kaur, Inderpreet Kaur . Validation of Software Quality Models using Machine Learning: An Empirical Study. 8th National Conference on Next generation Computing Technologies and Applications. NGCTA, 1 (November 2013), 1-7.

@article{
author = { Surbhi Gaur, Savleen Kaur, Inderpreet Kaur },
title = { Validation of Software Quality Models using Machine Learning: An Empirical Study },
journal = { 8th National Conference on Next generation Computing Technologies and Applications },
issue_date = { November 2013 },
volume = { NGCTA },
number = { 1 },
month = { November },
year = { 2013 },
issn = 0975-8887,
pages = { 1-7 },
numpages = 7,
url = { /proceedings/ngcta/number1/14189-1302/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 8th National Conference on Next generation Computing Technologies and Applications
%A Surbhi Gaur
%A Savleen Kaur
%A Inderpreet Kaur
%T Validation of Software Quality Models using Machine Learning: An Empirical Study
%J 8th National Conference on Next generation Computing Technologies and Applications
%@ 0975-8887
%V NGCTA
%N 1
%P 1-7
%D 2013
%I International Journal of Computer Applications
Abstract

Software Quality is that significant nonfunctional requirement which is not fulfilled by many software products. In order to identify the faulty classes we can use prediction models using object oriented metrics. This paper empirically analyses the relationship between object oriented metrics and fault proneness of NASA Data sets using six machine Learning classifiers. It has been exhibited that Random Forest provides optimum values for accuracy, precision, sensitivity and specificity by performing Multivariate analysis of NASA Data sets.

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Index Terms

Computer Science
Information Sciences

Keywords

Object-oriented Software Metrics Quality Metrics Classifiers Roc Fault Proneness.