Process algebra and probabilistic methods : performance modelling and verification : Joint International Workshop, PAPM-PROBMIV 2001, Aachen, Germany, September 12-14, 2001 : proceedings
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Bibliographic Information
Process algebra and probabilistic methods : performance modelling and verification : Joint International Workshop, PAPM-PROBMIV 2001, Aachen, Germany, September 12-14, 2001 : proceedings
(Lecture notes in computer science, 2165)
Springer, c2001
Available at / 25 libraries
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Library, Research Institute for Mathematical Sciences, Kyoto University数研
L/N||LNCS||216501041492
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University of Tsukuba Library, Library on Library and Information Science
007.08:L-49:2165011004060
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Including bibliographical references and index
Description and Table of Contents
Description
This book constitutes the refereed proceedings of the Joint Workshop on Process Algebra and Performance Modeling and Probabilistic Methods in Verification, PAPM-PROBMIV 2001, held in Aachen, Germany in September 2001.
The 12 revised full papers presented together with one invited paper were carefully reviewed and selected from 23 submissions. Among the topics addressed are model representation, model checking, probabilistic systems analysis, refinement, Markov chains, random variables, stochastic timed systems, Max-Plus algebra, process algebra, system modeling, and the Mobius modeling framework.
Table of Contents
Invited Paper.- Advances in Model Representations.- Contributed Papers.- Faster and Symbolic CTMC Model Checking.- Reachability Analysis of Probabilistic Systems by Successive Refinements.- Beyond Memoryless Distributions: Model Checking Semi-Markov Chains.- Coin Lemmas with Random Variables.- MoDeST - A Modelling and Description Language for Stochastic Timed Systems.- Randomization Helps in LTL Model Checking.- An Efficient Kronecker Representation for PEPA Models.- Reward Based Congruences: Can We Aggregate More?.- Using Max-Plus Algebra for the Evaluation of Stochastic Process Algebra Prefixes.- Expressing Processes with Different Action Durations through Probabilities.- Quantifying the Dynamic Behavior of Process Algebras.- Implementing a Stochastic Process Algebra within the Moebius Modeling Framework.
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