Validation of Stochastic Systems: A Guide to Current Research

Ana Sokolova, Erik P. de Vink (auth.), Christel Baier, Boudewijn R. Haverkort, Holger Hermanns, Joost-Pieter Katoen, Markus Siegle (eds.)3540222650, 9783540222651, 9783540246114

This tutorial volume presents a coherent and well-balanced introduction to the validation of stochastic systems; it is based on a GI/Dagstuhl research seminar. Supervised by the seminar organizers and volume editors, established researchers in the area as well as graduate students put together a collection of articles competently covering all relevant issues in the area.

The lectures are organized in topical sections on: modeling stochastic systems, model checking of stochastic systems, representing large state spaces, deductive verification of stochastic systems.

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Table of contents :
Front Matter….Pages –
Probabilistic Automata: System Types, Parallel Composition and Comparison….Pages 1-43
Tutte le Algebre Insieme: Concepts, Discussions and Relations of Stochastic Process Algebras with General Distributions….Pages 44-88
An Overview of Probabilistic Process Algebras and Their Equivalences….Pages 89-123
Verifying Qualitative Properties of Probabilistic Programs….Pages 124-146
On Probabilistic Computation Tree Logic….Pages 147-188
Model Checking for Probabilistic Timed Systems….Pages 189-229
Serial Disk-Based Analysis of Large Stochastic Models….Pages 230-255
Kronecker Based Matrix Representations for Large Markov Models….Pages 256-295
Symbolic Representations and Analysis of Large Probabilistic Systems….Pages 296-338
Probabilistic Methods in State Space Analysis….Pages 339-383
Analysing Randomized Distributed Algorithms….Pages 384-418
An Abstraction Framework for Mixed Non-deterministic and Probabilistic Systems….Pages 419-444
The Verification of Probabilistic Lossy Channel Systems….Pages 445-465
Back Matter….Pages –