Probabilistic Analysis of Binary Sessions
Omar Inverso, Hernán, Melgratti, Luca Padovani, Catia Trubiani, Emilio Tuosto · Institutional Research Information System University of Turin (University of Turin) · 2020
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.