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arXiv · 1808.08655

A Parametric Framework for Reversible Pi-Calculi

Doriana Medic·Claudio Antares Mezzina·Iain Phillips·Nobuko Yoshida
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Abstract

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.

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Doriana Medic, Claudio Antares Mezzina, Iain Phillips, Nobuko Yoshida. 2018-08-27. A Parametric Framework for Reversible Pi-Calculi. https://doi.org/10.4204/eptcs.276.8

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