Bounded Model Checking Using Satisfiability Solving
Formal Methods in System Design
Elements of Software Science (Operating and programming systems series)
Elements of Software Science (Operating and programming systems series)
Verification and planning for stochastic processes with asynchronous events
Verification and planning for stochastic processes with asynchronous events
Numerical vs. statistical probabilistic model checking
International Journal on Software Tools for Technology Transfer (STTT)
Statistical probabilistic model checking with a focus on time-bounded properties
Information and Computation
HVC '08 Proceedings of the 4th International Haifa Verification Conference on Hardware and Software: Verification and Testing
A Bayesian Approach to Model Checking Biological Systems
CMSB '09 Proceedings of the 7th International Conference on Computational Methods in Systems Biology
Bayesian statistical model checking with application to Simulink/Stateflow verification
Proceedings of the 13th ACM international conference on Hybrid systems: computation and control
Air-fuel ratio control in a gasoline engine
International Journal of Systems Science - Computational Intelligence for Modelling and Control of Advanced Automotive Drivetrains
PRISM 4.0: verification of probabilistic real-time systems
CAV'11 Proceedings of the 23rd international conference on Computer aided verification
Adaptive mobile checkpointing facility for wireless sensor networks
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part II
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As more computing systems are utilized in various areas of our society, the reliability of computing systems becomes a significant issue. However, as the complexity of computing systems increases, conventional verification and validation techniques such as testing and model checking have limitations to assess reliability of complex safety critical systems. Such systems often control highly complex continuous dynamics to interact with physical environments. To assure the reliability of safety critical hybrid systems, statistical model checking (SMC) techniques have been proposed. SMC techniques approximately compute probabilities for a target system to satisfy given requirements based on randomly sampled execution traces. In this paper, we empirically evaluated four state-ofthe- art SMC techniques on a fault-tolerant fuel control system in the automobile domain. Through the experiments, we could demonstrate that SMC is practically useful to assure the reliability of a safety critical hybrid system and we compared pros and cons of the four different SMC techniques.