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Subtyping Context-Free Session Types

Authors Gil Silva , Andreia Mordido , Vasco T. Vasconcelos

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ACM Subject Classification
  • Theory of computation → Type structures
  • Theory of computation → Concurrency
  • Software and its engineering → Concurrent programming structures
Keywords
  • Session types
  • Subtyping
  • Simulation
  • Simple grammars
  • Non-regular recursion

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Abstract

Context-free session types describe structured patterns of communication on heterogeneously typed channels, allowing the specification of protocols unconstrained by tail recursion. The enhanced expressive power provided by non-regular recursion comes, however, at the cost of the decidability of subtyping, even if equivalence is still decidable. We present an approach to subtyping context-free session types based on a novel kind of observational preorder we call XYZW-simulation, which generalizes XY-simulation (also known as covariant-contravariant simulation) and therefore also bisimulation and plain simulation. We further propose a subtyping algorithm that we prove to be sound, and present an empirical evaluation in the context of a compiler for a programming language. Due to the general nature of the simulation relation upon which it is built, this algorithm may also find applications in other domains.

Cite As Get BibTex

Gil Silva, Andreia Mordido, and Vasco T. Vasconcelos. Subtyping Context-Free Session Types. In 34th International Conference on Concurrency Theory (CONCUR 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 279, pp. 11:1-11:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023) https://doi.org/10.4230/LIPIcs.CONCUR.2023.11

Author Details

Gil Silva
  • LASIGE, Faculdade de Ciências da Universidade de Lisboa, Portugal
Andreia Mordido
  • LASIGE, Faculdade de Ciências da Universidade de Lisboa, Portugal
Vasco T. Vasconcelos
  • LASIGE, Faculdade de Ciências da Universidade de Lisboa, Portugal

Funding

Support for this research was provided by the Fundação para a Ciência e a Tecnologia through project SafeSessions, ref. PTDC/CCI-COM/6453/2020, and by the LASIGE Research Unit, ref. UIDB/00408/2020 and ref. UIDP/00408/2020.

Acknowledgements

We thank Luca Padovani, Diana Costa, Diogo Poças and the anonymous reviewers for their insightful comments.

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