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An Abstraction Framework for Mixed Non-deterministic and Probabilistic Systems

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Validation of Stochastic Systems

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2925))

Abstract

We study abstraction techniques for model checking systems that combine non-deterministic with probabilistic behavior, emphasizing the discrete case. Existing work on abstraction offers a host of isolated techniques which we discuss uniformly through the formulation of abstracted model-checking problems (MCPs). Although this conceptualization is primarily meant to be a useful focal point for surveying the literature on abstraction-based model checking even beyond such combined systems, it also opens up new research opportunities and challenges for abstract model checking of mixed systems. In particular, we sketch how quantitative domain theory may be used to specify the precision of answers obtained from abstract model checks.

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  1. Department of Computing, Imperial College London, South Kensington Campus, London, SW7 2AZ, United Kingdom

    Michael Huth

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  1. Michael Huth
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Editors and Affiliations

  1. Institute for Theoretical Computer Science, Technical University Dresden, Germany

    Christel Baier

  2. Centre for Telematics and Information Technology, Faculty for Electrical Engineering, Mathematics and Computer Science, University of Twente, P.O. Box 217, 7500, AE, Netherlands

    Boudewijn R. Haverkort

  3. VASY, INRIA, Grenoble Rhône-Alpes, France

    Holger Hermanns

  4. Software Modeling and Verification, RWTH Aachen University, Germany

    Joost-Pieter Katoen

  5. Institut für Technische Informatik, Universität der Bundeswehr München,  

    Markus Siegle

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Huth, M. (2004). An Abstraction Framework for Mixed Non-deterministic and Probabilistic Systems. In: Baier, C., Haverkort, B.R., Hermanns, H., Katoen, JP., Siegle, M. (eds) Validation of Stochastic Systems. Lecture Notes in Computer Science, vol 2925. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24611-4_12

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