Probabilistic programming semantics for name generation
Marcin Sabok, Sam Staton, Dario Stein, Michael Wolman
2021Year
2Citations
4Top-tier citations
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 ‘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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