Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
Zero-suppressed BDDs for set manipulation in combinatorial problems
DAC '93 Proceedings of the 30th international Design Automation Conference
Performance and reliability analysis of computer systems: an example-based approach using the SHARPE software package
Performance Modelling with Deterministic and Stochostic Petri Nets
Performance Modelling with Deterministic and Stochostic Petri Nets
The Möbius Framework and Its Implementation
IEEE Transactions on Software Engineering
OpenSESAME Simple but Extensive Structured Availability Modeling Environment
QEST '05 Proceedings of the Second International Conference on the Quantitative Evaluation of Systems
Analysis of Markov reward models using zero-suppressed multi-terminal BDDs
valuetools '06 Proceedings of the 1st international conference on Performance evaluation methodolgies and tools
Quantitative Analysis With the Probabilistic Model Checker PRISM
Electronic Notes in Theoretical Computer Science (ENTCS)
Stochastic dependability analysis of system architecture based on UML models
Architecting dependable systems
Proceedings of the 2nd international conference on Performance evaluation methodologies and tools
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The tool OpenSESAME offers an easy-to-use modeling framework which enables realistic availability and reliability analysis of fault-tolerant systems. Our symbolic engine, which is based on an extension of binary decision diagrams (BDDs), is capable of analyzing Markov reward models consisting of more than 108 system states. In this paper, we introduce a tool chain where OpenSESAME is employed for specifying models of fault-tolerant systems, and at the back end our symbolic engine is employed for carrying out numerical Markov reward analysis. For illustrating the applicability of this approach, we analyze a model of a fault-tolerant telecommunication service system with N redundant modules, where the system is available as long as at least K modules are available. Based on this model, it is shown, that the suggested tool chain has more modeling power than traditional combinatorial methods, e.g. simple reliability block diagrams or fault trees, is still easy-to-use if compared to other high-level model description techniques, and allows the analysis of complex system models where other tools fail.