A linear process-algebraic format with data for probabilistic automata

Authors:
Joost-Pieter Katoen;Jaco van de Pol;Mariëlle Stoelinga;Mark Timmer
Affiliations:
Formal Methods and Tools, Faculty of EEMCS, University of Twente, The Netherlands and Software Modeling and Verification, RWTH Aachen University, Germany;Formal Methods and Tools, Faculty of EEMCS, University of Twente, The Netherlands;Formal Methods and Tools, Faculty of EEMCS, University of Twente, The Netherlands;Formal Methods and Tools, Faculty of EEMCS, University of Twente, The Netherlands
Venue:
Theoretical Computer Science
Year:
2012

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Abstract

This paper presents a novel linear process-algebraic format for probabilistic automata. The key ingredient is a symbolic transformation of probabilistic process algebra terms that incorporate data into this linear format while preserving strong probabilistic bisimulation. This generalises similar techniques for traditional process algebras with data, and - more importantly - treats data and data-dependent probabilistic choice in a fully symbolic manner, leading to the symbolic analysis of parameterised probabilistic systems. We discuss several reduction techniques that can easily be applied to our models. A validation of our approach on two benchmark leader election protocols shows reductions of more than an order of magnitude.