1808.08655v1.pdf (251.93 kB)
Download file

A Parametric Framework for Reversible pi-Calculi

Download (251.93 kB)
journal contribution
posted on 04.02.2019, 12:22 by 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.

History

Citation

Electronic Proceedings in Theoretical Computer Science, 2018 (276), pp. 87-103 (17)

Author affiliation

/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Informatics

Version

VoR (Version of Record)

Published in

Electronic Proceedings in Theoretical Computer Science

Publisher

Open Publishing Association

issn

2075-2180

Copyright date

2018

Available date

04/02/2019

Publisher version

https://arxiv.org/abs/1808.08655v1

Language

en