Model Checking of Infinite State Space Markov Chains by Stochastic Bounds
ASMTA '08 Proceedings of the 15th international conference on Analytical and Stochastic Modeling Techniques and Applications
Weak Stochastic Comparisons for Performability Verification
ASMTA '09 Proceedings of the 16th International Conference on Analytical and Stochastic Modeling Techniques and Applications
Bisimulation minimisation mostly speeds up probabilistic model checking
TACAS'07 Proceedings of the 13th international conference on Tools and algorithms for the construction and analysis of systems
Three-valued abstraction for continuous-time Markov chains
CAV'07 Proceedings of the 19th international conference on Computer aided verification
Closed form absorption time bounds
EPEW'07 Proceedings of the 4th European performance engineering conference on Formal methods and stochastic models for performance evaluation
A tool to model traffic aggregation in networks of reconfigurable optical ADD/DROP multiplexers
VECoS'11 Proceedings of the Fifth international conference on Verification and Evaluation of Computer and Communication Systems
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Continuous-time Markov chains (CTMCs) have been largely applied with combination of high-level model specification techniques as performance evaluation and dependability, reliability analysis models for computer and communication systems. These models can be complemented by probabilistic model checking formalisms based on temporal logic to specify the guarantees on the measures of interest. We consider in this paper Continuous Stochastic Logic (CSL) which lets to express real-time probabilistic properties on CTMCs. It has been shown that the CSL operators can be checked by means of transient or steady-state analysis of the underlying CTMC. Since models are checked to see if the considered measures are guaranteed or not, bounding techniques are useful in probabilistic model checking. We propose to apply Stochastic Comparison technique to construct bounding models having a special structure which provides closed-form solutions to compute both transient and steady-state distributions. We present an algorithm to provide rapid model checking by means of these closed-form bounding distributions. Obviously, bounding distributions may not let to decide if the underlying model meets the probability thresholds or not. However in the case where the model can be checked by the proposed method, we gain significantly in time and memory complexity.