Automatic verification of finite-state concurrent systems using temporal logic specifications
ACM Transactions on Programming Languages and Systems (TOPLAS)
Theoretical Computer Science
The complexity of probabilistic verification
Journal of the ACM (JACM)
Dynamic Programming and Optimal Control, Two Volume Set
Dynamic Programming and Optimal Control, Two Volume Set
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Automatic verification of real-time systems with discrete probability distributions
Theoretical Computer Science
Symbolic Model Checking for Probabilistic Processes
ICALP '97 Proceedings of the 24th International Colloquium on Automata, Languages and Programming
Model Checking of Probabalistic and Nondeterministic Systems
Proceedings of the 15th Conference on Foundations of Software Technology and Theoretical Computer Science
Verifying Continuous Time Markov Chains
CAV '96 Proceedings of the 8th International Conference on Computer Aided Verification
Probabilistic Verification of Discrete Event Systems Using Acceptance Sampling
CAV '02 Proceedings of the 14th International Conference on Computer Aided Verification
Model checking for probability and time: from theory to practice
LICS '03 Proceedings of the 18th Annual IEEE Symposium on Logic in Computer Science
Directed explicit-state model checking in the validation of communication protocols
International Journal on Software Tools for Technology Transfer (STTT)
Probabilistic symbolic model checking with PRISM: a hybrid approach
International Journal on Software Tools for Technology Transfer (STTT) - Special section on tools and algorithms for the construction and analysis of systems
Model checking for a probabilistic branching time logic with fairness
Distributed Computing
Probabilistic model checking in practice: case studies with PRISM
ACM SIGMETRICS Performance Evaluation Review
Performance analysis of probabilistic timed automata using digital clocks
Formal Methods in System Design
Numerical vs. statistical probabilistic model checking
International Journal on Software Tools for Technology Transfer (STTT)
A formal analysis of bluetooth device discovery
International Journal on Software Tools for Technology Transfer (STTT)
Symbolic model checking for probabilistic timed automata
Information and Computation
Quantitative Analysis With the Probabilistic Model Checker PRISM
Electronic Notes in Theoretical Computer Science (ENTCS)
SFM'07 Proceedings of the 7th international conference on Formal methods for performance evaluation
Extended directed search for probabilistic timed reachability
FORMATS'06 Proceedings of the 4th international conference on Formal Modeling and Analysis of Timed Systems
Probabilistic model checking of complex biological pathways
CMSB'06 Proceedings of the 2006 international conference on Computational Methods in Systems Biology
On statistical model checking of stochastic systems
CAV'05 Proceedings of the 17th international conference on Computer Aided Verification
Stochastic transition systems for continuous state spaces and non-determinism
FOSSACS'05 Proceedings of the 8th international conference on Foundations of Software Science and Computation Structures
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
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Automated verification is a technique for establishing if certain properties, usually expressed in temporal logic, hold for a system model. The model can be defined using a high-level formalism or extracted directly from software using methods such as abstract interpretation. The verification proceeds through exhaustive exploration of the state-transition graph of the model and is therefore more powerful than testing. Quantitative verification is an analogous technique for establishing quantitative properties of a system model, such as the probability of battery power dropping below minimum, the expected time for message delivery and the expected number of messages lost before protocol termination. Models analysed through this method are typically variants of Markov chains, annotated with costs and rewards that describe resources and their usage during execution. Properties are expressed in temporal logic extended with probabilistic and reward operators. Quantitative verification involves a combination of a traversal of the state-transition graph of the model and numerical computation. This paper gives a brief overview of current research in quantitative verification, concentrating on the potential of the method and outlining future challenges. The modelling approach is described and the usefulness of the methodology illustrated with an example of a real-world protocol standard - Bluetooth device discovery - that has been analysed using the PRISM model checker (www.prismmodelchecker.org).