Symbolic partition refinement with automatic balancing of time and space
Performance Evaluation
The how and why of interactive Markov chains
FMCO'09 Proceedings of the 8th international conference on Formal methods for components and objects
Correctness issues of symbolic bisimulation computation for markov chains
MMB&DFT'10 Proceedings of the 15th international GI/ITG conference on Measurement, Modelling, and Evaluation of Computing Systems and Dependability and Fault Tolerance
Model checking interactive markov chains
TACAS'10 Proceedings of the 16th international conference on Tools and Algorithms for the Construction and Analysis of Systems
Quantitative timed analysis of interactive markov chains
NFM'12 Proceedings of the 4th international conference on NASA Formal Methods
Model checking of scenario-aware dataflow with CADP
DATE '12 Proceedings of the Conference on Design, Automation and Test in Europe
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Software and system dependability is getting ever more important in embedded system design. Current industrial practice of model-based analysis is supported by state-transition diagrammatic notations such as Statecharts. State-of-the-art modelling tools like Statemate support safety and failure-effect analysis at design time, but restricted to qualitative properties. This paper reports on a (plug-in) extension of Statemate enabling the evaluation of quantitative dependability properties at design time. The extension is compositional in the way the model is augmented with probabilistic timing information. This fact is exploited in the construction of the underlying mathematical model, a uniform continuous-time Markov decision process, on which we are able to check requirements of the form: "The probability to hit a safety-critical system configuration within a mission time of 3 hours is at most 0.01." We give a detailed explanation of the construction and evaluation steps making this possible, and report on a nontrivial case study of a high-speed train signalling system where the tool has been applied successfully.