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Reseach Article

Article:Fault Prediction Model by Fuzzy Profile Development of Reliability Relevant Software Metrics

by Ajeet Kumar Pandey, Neeraj Kumar Goyal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 11 - Number 6
Year of Publication: 2010
Authors: Ajeet Kumar Pandey, Neeraj Kumar Goyal
10.5120/1584-2124

Ajeet Kumar Pandey, Neeraj Kumar Goyal . Article:Fault Prediction Model by Fuzzy Profile Development of Reliability Relevant Software Metrics. International Journal of Computer Applications. 11, 6 ( December 2010), 34-41. DOI=10.5120/1584-2124

@article{ 10.5120/1584-2124,
author = { Ajeet Kumar Pandey, Neeraj Kumar Goyal },
title = { Article:Fault Prediction Model by Fuzzy Profile Development of Reliability Relevant Software Metrics },
journal = { International Journal of Computer Applications },
issue_date = { December 2010 },
volume = { 11 },
number = { 6 },
month = { December },
year = { 2010 },
issn = { 0975-8887 },
pages = { 34-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume11/number6/1584-2124/ },
doi = { 10.5120/1584-2124 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:59:53.217431+05:30
%A Ajeet Kumar Pandey
%A Neeraj Kumar Goyal
%T Article:Fault Prediction Model by Fuzzy Profile Development of Reliability Relevant Software Metrics
%J International Journal of Computer Applications
%@ 0975-8887
%V 11
%N 6
%P 34-41
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents a fault prediction model using reliability relevant software metrics and fuzzy inference system. For this a new approach is discussed to develop fuzzy profile of software metrics which are more relevant for software fault prediction. The proposed model predicts the fault density at the end of each phase of software development using relevant software metrics. On the basis of fault density at the end of testing phase, total number of faults in the software is predicted. The model seems to useful for both software engineer as well as project manager to optimally allocate resources and achieve more reliable software within the time and cost constraints. To validate the prediction accuracy, the model results are validated using PROMISE Software Engineering Repository Data set.

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Index Terms

Computer Science
Information Sciences

Keywords

Reliability Relevant Software Metrics Software Fault Prediction Fault Density Fuzzy profile Fuzzy Inference System (FIS)