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International Conference on Algebraic Methodology and Software Technology

AMAST 2010: Algebraic Methodology and Software Technology pp 1–27Cite as

Structural Analysis for Stochastic Process Algebra Models

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 6486))

Abstract

Stochastic process algebra models have been successfully used in the area of performance modelling for the last twenty years, and more recently have been adopted for modelling biochemical processes in systems biology. Most research on these modelling formalisms has been on quantitative analysis, particularly the derivation of quantified dynamic information about the system modelled in the face of the state space explosion problem. In this paper we instead consider qualitative analysis, looking at how recent developments to tackle state space explosion in quantified analysis can be also harnessed to establish properties such as freedom from deadlock in an efficient manner.

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Author information

Authors and Affiliations

  1. School of Information Engineering, Yangzhou University, Yangzhou, 225009, China

    Jie Ding

  2. LFCS, School of Informatics, Edinburgh University, UK

    Jane Hillston

Authors
  1. Jie Ding
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  2. Jane Hillston
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Editor information

Editors and Affiliations

  1. Macquarie University, Sydney, Australia

    Michael Johnson

  2. University of Oxford, Oxford, UK

    Dusko Pavlovic

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Ding, J., Hillston, J. (2011). Structural Analysis for Stochastic Process Algebra Models. In: Johnson, M., Pavlovic, D. (eds) Algebraic Methodology and Software Technology. AMAST 2010. Lecture Notes in Computer Science, vol 6486. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17796-5_1

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  • DOI: https://doi.org/10.1007/978-3-642-17796-5_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17795-8

  • Online ISBN: 978-3-642-17796-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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