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Probabilistic Analysis of Binary Sessions

Authors Omar Inverso , Hernán Melgratti , Luca Padovani , Catia Trubiani , Emilio Tuosto



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Author Details

Omar Inverso
  • Gran Sasso Science Institute, L'Aquila, Italy
Hernán Melgratti
  • ICC, Universidad de Buenos Aires, Conicet, Argentina
Luca Padovani
  • Università di Torino, Italy
Catia Trubiani
  • Gran Sasso Science Institute, L'Aquila, Italy
Emilio Tuosto
  • Gran Sasso Science Institute, L'Aquila, Italy

Acknowledgements

#2{The authors are grateful to the anonymous reviewers for their detailed feedback. }

Cite AsGet BibTex

Omar Inverso, Hernán Melgratti, Luca Padovani, Catia Trubiani, and Emilio Tuosto. Probabilistic Analysis of Binary Sessions. In 31st International Conference on Concurrency Theory (CONCUR 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 171, pp. 14:1-14:21, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2020)
https://doi.org/10.4230/LIPIcs.CONCUR.2020.14

Abstract

We study a probabilistic variant of binary session types that relate to a class of Finite-State Markov Chains. The probability annotations in session types enable the reasoning on the probability that a session terminates successfully, for some user-definable notion of successful termination. We develop a type system for a simple session calculus featuring probabilistic choices and show that the success probability of well-typed processes agrees with that of the sessions they use. To this aim, the type system needs to track the propagation of probabilistic choices across different sessions.

Subject Classification

ACM Subject Classification
  • Theory of computation → Type structures
Keywords
  • Probabilistic choices
  • session types
  • static analysis
  • deadlock freedom

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