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International Conference on Formal Modeling and Analysis of Timed Systems

FORMATS 2015: Formal Modeling and Analysis of Timed Systems pp 206–221Cite as

Quantitative Analysis of Concurrent Reversible Computations

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9268))

Abstract

Reversible computing is a paradigm of computation that extends the standard forward-only programming to reversible programming, so that programs can be executed both in the standard, forward direction, and backward, going back to past states. In this paper we present novel quantitative stochastic model for concurrent and cooperatsible computations. More precisely, we introduce the class of \(\rho \) -reversible stochastic automata and define a semantics for the synchronization ensuring that this class of models is closed under composition. For this class of automata we give an efficient way of deriving the equilibrium distribution. Moreover, we prove that the equilibrium distribution of the composition of reversible automata can be derived as the product of the equilibrium distributions of each automaton in isolation.

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Authors and Affiliations

  1. DAIS, Università Ca’ Foscari Venezia, Via Torino, 155, Venezia, Italy

    Andrea Marin & Sabina Rossi

Authors
  1. Andrea Marin
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  2. Sabina Rossi
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Corresponding author

Correspondence to Sabina Rossi .

Editor information

Editors and Affiliations

  1. University of Colorado, Boulder, Colorado, USA

    Sriram Sankaranarayanan

  2. University of Florence, Florence, Italy

    Enrico Vicario

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Marin, A., Rossi, S. (2015). Quantitative Analysis of Concurrent Reversible Computations. In: Sankaranarayanan, S., Vicario, E. (eds) Formal Modeling and Analysis of Timed Systems. FORMATS 2015. Lecture Notes in Computer Science(), vol 9268. Springer, Cham. https://doi.org/10.1007/978-3-319-22975-1_14

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  • DOI: https://doi.org/10.1007/978-3-319-22975-1_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22974-4

  • Online ISBN: 978-3-319-22975-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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