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Assessing Software Quality with Time Domain Pareto Type II using SPC

by K. Sita Kumari, R. Satya Prasad
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 85 - Number 19
Year of Publication: 2014
Authors: K. Sita Kumari, R. Satya Prasad
10.5120/15100-3523

K. Sita Kumari, R. Satya Prasad . Assessing Software Quality with Time Domain Pareto Type II using SPC. International Journal of Computer Applications. 85, 19 ( January 2014), 46-52. DOI=10.5120/15100-3523

@article{ 10.5120/15100-3523,
author = { K. Sita Kumari, R. Satya Prasad },
title = { Assessing Software Quality with Time Domain Pareto Type II using SPC },
journal = { International Journal of Computer Applications },
issue_date = { January 2014 },
volume = { 85 },
number = { 19 },
month = { January },
year = { 2014 },
issn = { 0975-8887 },
pages = { 46-52 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume85/number19/15100-3523/ },
doi = { 10.5120/15100-3523 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:02:56.992672+05:30
%A K. Sita Kumari
%A R. Satya Prasad
%T Assessing Software Quality with Time Domain Pareto Type II using SPC
%J International Journal of Computer Applications
%@ 0975-8887
%V 85
%N 19
%P 46-52
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

As the usage of software is getting increased day by day, there is a need for software reliability and for this several software reliability growth models exist that are capable of finding the occurrence of errors. It is also possible to find the reliability of time domain models based on order statistics with Non-Homogeneous Poisson Process (NHPP). The conditional failure rate is an important factor for software and order statistics can be used in various applications like characterization of problems, detecting outliers, linear estimation, study of system reliability, life testing, survival analysis, data compression and many others. Using Statistical Process Control (SPC), we can monitor when the software failures occurs, that helps in improving the reliability of software. In this paper, we proposed a control mechanism Pareto Type II model with an on order statistics based on NHPP and the observations are considered for time domain failure data. The unknown parameters are estimated using a well-known estimation method known as Maximum Likelihood Estimation (MLE). The model is analyzed using live data sets.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Order Statistics Statistical Process Control Pareto Type II NHPP MLE Control charts.

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