2018/08/27 by Doriana Medic, Claudio Antares Mezzina, Iain Phillips +1
Computer Science · #cs.FL
paper · pdf · doi:10.4204/eptcs.276.8
published as EPTCS 276, 2018, pp. 87-103 · In Proceedings EXPRESS/SOS 2018, arXiv:1808.08071. A full version of this paper, containing all proofs, appears as arXiv:1807.11800
arxiv created 2018/08/27 · arxiv updated 2018/08/28
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.