Probabilistic programming semantics for name generation

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Abstract

We make a formal analogy between random sampling and fresh name generation. We show that quasi-Borel spaces, a model for probabilistic programming, can soundly interpret the ν-calculus, a calculus for name generation. Moreover, we prove that this semantics is fully abstract up to first-order types. This is surprising for an g 'off-the-shelf' model, and requires a novel analysis of probability distributions on function spaces. Our tools are diverse and include descriptive set theory and normal forms for the ν-calculus.

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APA

Sabok, M., Staton, S., Stein, D., & Wolman, M. (2021). Probabilistic programming semantics for name generation. Proceedings of the ACM on Programming Languages, 5(POPL). https://doi.org/10.1145/3434292

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