A Parametric Framework for Reversible Pi-Calculi
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.
Cite
@article{arxiv.1808.08655,
title = {A Parametric Framework for Reversible Pi-Calculi},
author = {Doriana Medic and Claudio Antares Mezzina and Iain Phillips and Nobuko Yoshida},
journal= {arXiv preprint arXiv:1808.08655},
year = {2018}
}
Comments
In Proceedings EXPRESS/SOS 2018, arXiv:1808.08071. A full version of this paper, containing all proofs, appears as arXiv:1807.11800