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  • 标题:Probabilistic Analysis of Binary Sessions
  • 本地全文:下载
  • 作者:Omar Inverso ; Hern{'a}n Melgratti ; Luca Padovani
  • 期刊名称:LIPIcs : Leibniz International Proceedings in Informatics
  • 电子版ISSN:1868-8969
  • 出版年度:2020
  • 卷号:171
  • 页码:14:1-14:21
  • DOI:10.4230/LIPIcs.CONCUR.2020.14
  • 出版社:Schloss Dagstuhl -- Leibniz-Zentrum fuer Informatik
  • 摘要: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.
  • 关键词:Probabilistic choices; session types; static analysis; deadlock freedom
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