Reliability of Systems with Markov Transfer of Control, II
IEEE Transactions on Software Engineering
A New Approach to the Modeling of Recovery Block Structures
IEEE Transactions on Software Engineering
A Markov Chain Model for Statistical Software Testing
IEEE Transactions on Software Engineering
Modular Operational Test Plans for Inferences on Software Reliability Based on a Markov Model
IEEE Transactions on Software Engineering
Planning and Certifying Software System Reliability
IEEE Software
Formal Limits on Determining Reliabilities of Component-Based Software Systems
ISSRE '00 Proceedings of the 11th International Symposium on Software Reliability Engineering
Sensitivity analysis for a scenario-based reliability prediction model
WADS '05 Proceedings of the 2005 workshop on Architecting dependable systems
A Simulation Approach to Structure-Based Software Reliability Analysis
IEEE Transactions on Software Engineering
Sensitivity of software system reliability to usage profile changes
Proceedings of the 2007 ACM symposium on Applied computing
Architecture-Based Software Reliability Analysis: Overview and Limitations
IEEE Transactions on Dependable and Secure Computing
Extracting test sequences from a Markov software usage model by ACO
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
A Bayesian model for predicting reliability of software systems at the architectural level
QoSA'07 Proceedings of the Quality of software architectures 3rd international conference on Software architectures, components, and applications
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Software/hardware systems are considered which can be decomposed into a finite number of modules. It is assumed that control of the system is transferred among the modules according to a Markov process. Each module has an associated reliability which gives the probability that the module will operate correctly when called and will transfer control successfully when finished. The system will eventually either fail or complete its task successfully and enter a terminal state. The reliability of the system is studied in terms of the module reliabilities and the transition probabilities. Improved methods of predicting system reliability, allocating module reliability, and determining module sensitivity are developed. Special branching and sequential systems are studied in detail.