Exponential order statistic models of software reliability growth
IEEE Transactions on Software Engineering
Software reliability: measurement, prediction, application
Software reliability: measurement, prediction, application
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Handbook of software reliability engineering
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IEEE Software
A Unified Scheme of Some Nonhomogenous Poisson Process Models for Software Reliability Estimation
IEEE Transactions on Software Engineering
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FTCS '98 Proceedings of the The Twenty-Eighth Annual International Symposium on Fault-Tolerant Computing
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ISSRE '97 Proceedings of the Eighth International Symposium on Software Reliability Engineering
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ISSRE '98 Proceedings of the The Ninth International Symposium on Software Reliability Engineering
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ISSRE '00 Proceedings of the 11th International Symposium on Software Reliability Engineering
Software field failure rate prediction before software deployment
Journal of Systems and Software
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IEEE Transactions on Software Engineering
Software Reliability Growth Modeling: Models and Applications
IEEE Transactions on Software Engineering
Considering fault removal efficiency in software reliability assessment
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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This paper presents a SRGM (software reliability growth model) from testing to operation based on NHPP (nonhomogeneous Poisson process). Although a few research projects have been devoted to the differences between testing environment and operational environment, Consideration of the variation of environmental influence factors along testing time in the existing models is limited. The model in this paper is the first scheme of a few NHPP models that take environmental factors experimented from actual failure data as a function of testing time. FDR (fault detection rate) is usually used to measure the effectiveness of fault detection by test techniques and test cases. A bell-shaped FDR function of testing phase is proposed which integrate both environmental factors and inherent FDR per fault. A NHPP SRGM from testing to operation that incorporates environmental factors called TOE-SRGM is built which integrates the proposed FDR of testing phase and FDR function of operational phase. TOE-SRGM is evaluated using software failure data. The results show that the predictive power of TOE-SRGM is better than some of other SRGMs.