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• W2228964661 abstract "Probabilistic coupling is a powerful tool for analyzing pairs of probabilistic processes. Roughly, coupling two processes requires finding an appropriate witness process that models both processes in the same probability space. Couplings are powerful tools proving properties about the relation between two processes, include reasoning about convergence of distributions and stochastic dominance—a probabilistic version of a monotonicity property. While the mathematical definition of coupling looks rather complex and cumbersome to manipulate, we show that the relational program logic pRHL—the logic underlying the EasyCrypt cryptographic proof assistant—already internalizes a generalization of probabilistic coupling. With this insight, constructing couplings is no harder than constructing logical proofs. We demonstrate how to express and verify classic examples of couplings in pRHL, and we mechanically verify several couplings in EasyCrypt." @default.
• W2228964661 created "2016-06-24" @default.
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• W2228964661 date "2015-01-01" @default.
• W2228964661 modified "2023-10-04" @default.
• W2228964661 title "Relational Reasoning via Probabilistic Coupling" @default.
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• W2228964661 doi "https://doi.org/10.1007/978-3-662-48899-7_27" @default.
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