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DOI: 10.4230/LIPIcs.CONCUR.2020.14
Probabilistic Analysis of Binary Sessions

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

Published in: LIPIcs, Volume 171, 31st International Conference on Concurrency Theory (CONCUR 2020)

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.
Cite as

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)

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@InProceedings{inverso_et_al:LIPIcs.CONCUR.2020.14,
  author =	{Inverso, Omar and Melgratti, Hern\'{a}n and Padovani, Luca and Trubiani, Catia and Tuosto, Emilio},
  title =	{{Probabilistic Analysis of Binary Sessions}},
  booktitle =	{31st International Conference on Concurrency Theory (CONCUR 2020)},
  pages =	{14:1--14:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-160-3},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{171},
  editor =	{Konnov, Igor and Kov\'{a}cs, Laura},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.CONCUR.2020.14},
  URN =		{urn:nbn:de:0030-drops-128264},
  doi =		{10.4230/LIPIcs.CONCUR.2020.14},
  annote =	{Keywords: Probabilistic choices, session types, static analysis, deadlock freedom}
}
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