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Model checking for performability

Published online by Cambridge University Press:  08 July 2013

C. BAIER ,
E. M. HAHN ,
B. R. HAVERKORT ,
H. HERMANNS  and
J.-P. KATOEN
C. BAIER
Affiliation:
Technische Universität Dresden, Dresden, Germany Email: baier@tcs.inf.tu-dresden.de
E. M. HAHN
Affiliation:
Saarland University, Saarbrücken, Germany Email: hermanns@cs.uni-saarland.de; emh@cs.uni-saarland.de
B. R. HAVERKORT
Affiliation:
Embedded Systems Institute, Eindhoven, The Netherlands and University of Twente, Enschede, The Netherlands Email: brh@cs.utwente.nl
H. HERMANNS
Affiliation:
Saarland University, Saarbrücken, Germany Email: hermanns@cs.uni-saarland.de; emh@cs.uni-saarland.de
J.-P. KATOEN
Affiliation:
University of Twente, Enschede, The Netherlands and RWTH Aachen University, Aachen, Germany Email: katoen@cs.rwth-aachen.de
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Abstract

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This paper gives a bird's-eye view of the various ingredients that make up a modern, model-checking-based approach to performability evaluation: Markov reward models, temporal logics and continuous stochastic logic, model-checking algorithms, bisimulation and the handling of non-determinism. A short historical account as well as a large case study complete this picture. In this way, we show convincingly that the smart combination of performability evaluation with stochastic model-checking techniques, developed over the last decade, provides a powerful and unified method of performability evaluation, thereby combining the advantages of earlier approaches.

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