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.

@article{paperbot1150,
  title = {Probabilistic programming semantics for name generation},
  author = {Marcin Sabok and Sam Staton and Dario Stein and Michael Wolman},
  journal = {Proceedings of the ACM on Programming Languages},
  volume = {5},
  number = {POPL},
  year = {2021},
  doi = {10.1145/3434292}
}