Computing Poisson probabilities
Communications of the ACM
IEEE Transactions on Software Engineering - Special issue on formal methods in software practice
Model-checking continuous-time Markov chains
ACM Transactions on Computational Logic (TOCL)
On the Use of Model Checking Techniques for Dependability Evaluation
SRDS '00 Proceedings of the 19th IEEE Symposium on Reliable Distributed Systems
Model checking meets performance evaluation
ACM SIGMETRICS Performance Evaluation Review
Three-valued abstraction for continuous-time Markov chains
CAV'07 Proceedings of the 19th international conference on Computer aided verification
Ymer: a statistical model checker
CAV'05 Proceedings of the 17th international conference on Computer Aided Verification
PRISM: a tool for automatic verification of probabilistic systems
TACAS'06 Proceedings of the 12th international conference on Tools and Algorithms for the Construction and Analysis of Systems
Delayed continuous-time markov chains for genetic regulatory circuits
CAV'12 Proceedings of the 24th international conference on Computer Aided Verification
Time-Bounded Model Checking of Infinite-State Continuous-Time Markov Chains
Fundamenta Informaticae - Application of Concurrency to System Design
Bayesian statistical model checking with application to Stateflow/Simulink verification
Formal Methods in System Design
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The design of complex concurrent systems often involves intricate performance and dependability considerations. Continuous-time Markov chains (CTMCs) are a widely used modeling formalism, where performance and dependability properties are analyzable by model checking. We present INFAMY , a model checker for arbitrarily structured infinite-state CTMCs. It checks probabilistic timing properties expressible in continuous stochastic logic (CSL). Conventional model checkers explore the given model exhaustively, which is often costly, due to state explosion, and impossible if the model is infinite. INFAMY only explores the model up to a finite depth, with the depth bound being computed on-the-fly . The computation of depth bounds is configurable to adapt to the characteristics of different classes of models.