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Coupling proofs are probabilistic product programs

Abstract : Couplings are a powerful mathematical tool for reasoning about pairs of probabilistic processes. Recent developments in formal verification identify a close connection between couplings and pRHL, a relational program logic motivated by applications to provable security, enabling formal construction of couplings from the probability theory literature. However, existing work using pRHL merely shows existence of a coupling and does not give a way to prove quantitative properties about the coupling, which are need to reason about mixing and convergence of probabilistic processes. Furthermore, pRHL is inherently incomplete, and is not able to capture some advanced forms of couplings such as shift couplings. We address both problems as follows. First, we define an extension of pRHL, called ×pRHL, which explicitly constructs the coupling in a pRHL derivation in the form of a probabilistic product program that simulates two correlated runs of the original program. Existing verification tools for probabilistic programs can then be directly applied to the probabilistic product to prove quantitative properties of the coupling. Second, we equip ×pRHL with a new rule for while loops, where reasoning can freely mix synchronized and unsynchronized loop iterations. Our proof rule can capture examples of shift couplings, and the logic is relatively complete for deterministic programs. We show soundness of ×pRHL and use it to analyze two classes of examples. First, we verify rapid mixing using different tools from coupling: standard coupling, shift coupling, and path coupling, a compositional principle for combining local couplings into a global coupling. Second, we verify (approximate) equivalence between a source and an optimized program for several instances of loop optimizations from the literature.
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Contributor : Benjamin Gregoire <>
Submitted on : Monday, November 27, 2017 - 10:33:55 AM
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Gilles Barthe, Benjamin Grégoire, Justin Hsu, Pierre-Yves Strub. Coupling proofs are probabilistic product programs. POPL 2017 - Proceedings of the 44th ACM SIGPLAN Symposium on Principles of Programming Languages, Jan 2017, Paris, France. pp.161-174, ⟨10.1145/3009837.3009896⟩. ⟨hal-01649028⟩



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