Probabilistic Analysis of Binary Sessions

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. ACM Subject Classification Theory of computation → Type structuresKeywords and phrases Probabilistic choices; session types; static analysis; deadlock freedom.