info:eu-repo/semantics/article
Probabilistic analysis of binary sessions
Fecha
2020-08Registro en:
Inverso, Omar; Melgratti, Hernan Claudio; Padovani, Luca; Trubiani, Catia; Tuosto, Emilio; Probabilistic analysis of binary sessions; Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing; Leibniz International Proceedings in Informatics, LIPIcs; 171; 8-2020; 141-1421
1868-8969
CONICET Digital
CONICET
Autor
Inverso, Omar
Melgratti, Hernan Claudio
Padovani, Luca
Trubiani, Catia
Tuosto, Emilio
Resumen
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.