Discrete Nonhomogeneous Poisson Process Software Reliability Growth Models Based on Test Coverage

To incorporate the effect of test coverage, we proposed two novel discrete nonhomogeneous Poisson process software reliability growth models in this article using failure data and test coverage, which are both regarding the number of executed test cases instead of execution time. Because one of the...

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Bibliographic Details
Published in:Quality and reliability engineering international Vol. 29; no. 1; pp. 103 - 112
Main Authors: Wang, Shuanqi, Wu, Yumei, Lu, Minyan, Li, Haifeng
Format: Journal Article
Language:English
Published: Bognor Regis Blackwell Publishing Ltd 01.02.2013
Wiley Subscription Services, Inc
Subjects:
Beta
beta function
Fittings
imperfect debugging
Mathematical analysis
Mathematical models
nonhomogeneous Poisson process
Software reliability
software reliability growth model
test coverage function
ISSN:0748-8017, 1099-1638
Online Access:Get full text
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Summary:To incorporate the effect of test coverage, we proposed two novel discrete nonhomogeneous Poisson process software reliability growth models in this article using failure data and test coverage, which are both regarding the number of executed test cases instead of execution time. Because one of the most important factors of the coverage‐based software reliability growth models is the test coverage function (TCF), we first discussed a discrete TCF based on beta function. Then we developed two discrete mean value functions (MVF) integrating test coverage and imperfect debugging. Finally, the proposed discrete TCF and MVFs are evaluated and validated on two actual software reliability data sets. The results of numerical illustration demonstrate that the proposed TCF and the MVFs provide better estimation and fitting under comparisons. Copyright © 2012 John Wiley & Sons, Ltd.
Bibliography:ArticleID:QRE1301
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ISSN:0748-8017
1099-1638
DOI:10.1002/qre.1301