A compositional approach to performance modelling
A compositional approach to performance modelling
Model-checking continuous-time Markov chains
ACM Transactions on Computational Logic (TOCL)
Process algebra for performance evaluation
Theoretical Computer Science
Multi-Terminal Binary Decision Diagrams: An Efficient DataStructure for Matrix Representation
Formal Methods in System Design
Verification and planning for stochastic processes with asynchronous events
Verification and planning for stochastic processes with asynchronous events
APMC 3.0: Approximate Verification of Discrete and Continuous Time Markov Chains
QEST '06 Proceedings of the 3rd international conference on the Quantitative Evaluation of Systems
ICSOC '07 Proceedings of the 5th international conference on Service-Oriented Computing
PRISM: probabilistic model checking for performance and reliability analysis
ACM SIGMETRICS Performance Evaluation Review
MarCaSPiS: a Markovian Extension of a Calculus for Services
Electronic Notes in Theoretical Computer Science (ENTCS)
A calculus for orchestration of web services
ESOP'07 Proceedings of the 16th European conference on Programming
A tool for checking probabilistic properties of COWS services
TGC'10 Proceedings of the 5th international conference on Trustworthly global computing
A tool for checking probabilistic properties of COWS services
TGC'10 Proceedings of the 5th international conference on Trustworthly global computing
Simulation and analysis of distributed systems in klaim
COORDINATION'10 Proceedings of the 12th international conference on Coordination Models and Languages
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Given the description of a model and a probabilistic formula, approximate model checking is a verification technique based on statistical reasoning that allows answering whether or not the model satisfies the formula. Only a subset of the properties that can be analyzed by exact model checking can be attacked by approximate methods. These latest methods, though, being based on simulation and sampling have the advantage of not requiring the generation of the complete state-space of the model. Here we describe an efficient tool for the approximate model checking of services written in a stochastic variant of COWS, a process calculus for the orchestration of services.