Baier C., Haverkort B.R., Hermanns H., Katoen J.-P., Siegle M. (eds.) Validation of Stochastic Systems: A Guide to Current Research

Berlin: Springer, 2004. — 472 p.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.Probabilistic Automata: System Types, Parallel Composition and Comparison
Tutte le Algebre Insieme: Concepts, Discussions and Relations of Stochastic Process Algebras with General Distributions
An Overview of Probabilistic Process Algebras and Their Equivalences
Verifying Qualitative Properties of Probabilistic Programs
On Probabilistic Computation Tree Logic
Model Checking for Probabilistic Timed Systems
Serial Disk-Based Analysis of Large Stochastic Models
Kronecker Based Matrix Representations for Large Markov Models
Symbolic Representations and Analysis of Large Probabilistic Systems
Probabilistic Methods in State Space Analysis
Analyzing Randomized Distributed Algorithms
An Abstraction Framework for Mixed Non-deterministic and Probabilistic Systems
The Verification of Probabilistic Lossy Channel Systems