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Reseach Article

A Bivariate Autoregressive Software Reliability Model

by K.Vedavathi, K.Srinivas Rao, A.VinayBabu
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 38 - Number 7
Year of Publication: 2012
Authors: K.Vedavathi, K.Srinivas Rao, A.VinayBabu
10.5120/4699-6850

K.Vedavathi, K.Srinivas Rao, A.VinayBabu . A Bivariate Autoregressive Software Reliability Model. International Journal of Computer Applications. 38, 7 ( January 2012), 19-22. DOI=10.5120/4699-6850

@article{ 10.5120/4699-6850,
author = { K.Vedavathi, K.Srinivas Rao, A.VinayBabu },
title = { A Bivariate Autoregressive Software Reliability Model },
journal = { International Journal of Computer Applications },
issue_date = { January 2012 },
volume = { 38 },
number = { 7 },
month = { January },
year = { 2012 },
issn = { 0975-8887 },
pages = { 19-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume38/number7/4699-6850/ },
doi = { 10.5120/4699-6850 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:24:15.266048+05:30
%A K.Vedavathi
%A K.Srinivas Rao
%A A.VinayBabu
%T A Bivariate Autoregressive Software Reliability Model
%J International Journal of Computer Applications
%@ 0975-8887
%V 38
%N 7
%P 19-22
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Software reliability models play a dominant role in the analysis of failure data for real time command and control software systems. Goel and Okumoto model is a non homogenous Poisson Process software reliability growth model which has gained a lot of importance in software reliability analysis and prediction. The process of parameter estimation is the major drawback of this model because the independent nature of attribute values is considered in estimation. But in real world applications, there are correlations existing among the attributes. Keeping this criterion, a bivariate autoregressive model of order 1 which forms a linear combination of variants namely software faults and test workers is proposed. A numerical illustration is presented to evaluate the performance of the developed model with that of the existing univariate autoregressive models and found that the proposed model outperforms than exiting model in evaluating and predicting software reliability.

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Index Terms

Computer Science
Information Sciences

Keywords

Software Reliability Autoregressive Model Reliability Evolution