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.1807.11800,
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:1807.11800},
year = {2018}
}
Comments
Extended version of the EXPRESS2018 paper