Equivalence and Similarity Refutation for Probabilistic Programs

TL;DR

This paper introduces a fully automated, formal method for refuting equivalence and similarity of output distributions in probabilistic programs, applicable to infinite-state cases, with proven correctness guarantees.

Contribution

It presents the first automated approach using supermartingales for refuting probabilistic program equivalence and similarity with formal correctness guarantees.

Findings

Effective in refuting equivalence and similarity in various examples

Applicable to infinite-state probabilistic programs

Provides formal correctness guarantees

Abstract

We consider the problems of statically refuting equivalence and similarity of output distributions defined by a pair of probabilistic programs. Equivalence and similarity are two fundamental relational properties of probabilistic programs that are essential for their correctness both in implementation and in compilation. In this work, we present a new method for static equivalence and similarity refutation. Our method refutes equivalence and similarity by computing a function over program outputs whose expected value with respect to the output distributions of two programs is different. The function is computed simultaneously with an upper expectation supermartingale and a lower expectation submartingale for the two programs, which we show to together provide a formal certificate for refuting equivalence and similarity. To the best of our knowledge, our method is the first approach to relational program analysis to offer the combination of the following desirable features: (1) it is fully automated, (2) it is applicable to infinite-state probabilistic programs, and (3) it provides formal guarantees on the correctness of its results. We implement a prototype of our method and our experiments demonstrate the effectiveness of our method to refute equivalence and similarity for a number of examples collected from the literature.