Software reliability: measurement, prediction, application
Software reliability: measurement, prediction, application
Software Reliability Modelling and Identification
Software Reliability Modelling and Identification
Estimating the Probability of Failure When Testing Reveals No Failures
IEEE Transactions on Software Engineering
Compound-Poisson Software Reliability Model
IEEE Transactions on Software Engineering
Modeling Correlation in Software Recovery Blocks
IEEE Transactions on Software Engineering - Special issue on software reliability
Handbook of software reliability engineering
Handbook of software reliability engineering
Software reliability and system reliability
Handbook of software reliability engineering
Software reliability modeling survey
Handbook of software reliability engineering
Some Conservative Stopping Rules for the Operational Testing of Safety-Critical Software
IEEE Transactions on Software Engineering
Probability and Statistics with Reliability, Queuing and Computer Science Applications
Probability and Statistics with Reliability, Queuing and Computer Science Applications
Are We Testing for True Reliability?
IEEE Software
Integrating Time Domain and Input Domain Analyses of Software Reliability Using Tree-Based Models
IEEE Transactions on Software Engineering
An Introduction to Software Reliability Modelling
Software Reliability Modelling and Identification
Data partition based reliability modeling
ISSRE '96 Proceedings of the The Seventh International Symposium on Software Reliability Engineering
Software Reliability Status and Perspectives
IEEE Transactions on Software Engineering
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Perhaps the most stringent restriction that is present in most software reliability models is the assumption of independence among successive software failures. Our research was motivated by the fact that although there are practical situations in which this assumption could be easily violated, much of the published literature on software reliability modeling does not seriously address this issue.In this paper, we present a software reliability modeling framework based on Markov renewal processes which naturally introduces dependence among successive software runs. The presented approach enables the phenomena of failure clustering to be precisely characterized and its effects on software reliability to be analyzed. Furthermore, it also provides bases for a more flexible and consistent model formulation and solution. The Markov renewal model presented in this paper can be related to the existing software reliability growth models, that is, a number of them can be derived as special cases under the assumption of failure independence.Our future research is focused on developing more specific and detailed models within this framework, as well as statistical inference procedures for performing estimations and predictions based on the experimental data.