A Parametric Framework for Reversible Pi-Calculi

Doriana Medic
Claudio Antares Mezzina
Iain Phillips
Nobuko Yoshida

This paper presents a study of causality in a reversible, concurrent setting. There exist various notions of causality in pi-calculus, which differ in the treatment of parallel extrusions of the same name. In this paper we present a uniform framework for reversible pi-calculi that is parametric with respect to a data structure that stores information about an extrusion of a name. Different data structures yield different approaches to the parallel extrusion problem. We map three well-known causal semantics into our framework. We show that the (parametric) reversibility induced by our framework is causally-consistent and prove a causal correspondence between an appropriate instance of the framework and Boreale and Sangiorgi's causal semantics.

In Jorge A. Pérez and Simone Tini: Proceedings Combined 25th International Workshop on Expressiveness in Concurrency and 15th Workshop on Structural Operational Semantics (EXPRESS/SOS 2018), Beijing, China, September 3, 2018, Electronic Proceedings in Theoretical Computer Science 276, pp. 87–103.
A full version of this paper, containing all proofs, appears as https://arxiv.org/abs/1807.11800.
Published: 24th August 2018.

ArXived at: http://dx.doi.org/10.4204/EPTCS.276.8 bibtex PDF
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