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Caesar: A Deductive Verifier for Probabilistic Programs
Philipp Schröer, Kevin Batz, Umut YiÄit Dural +4
Caesar is a deductive verifier for probabilistic programs. At its core lies HeyVL, a quantitative intermediate verification language based on the real-valued logic HeyLo. HeyVL all…
Generating Functions Meet Occupation Measures: Invariant Synthesis for Probabilistic Loops (Extended Version)
Darion Haase, Kevin Batz, Adrian Gallus +4
A fundamental computational task in probabilistic programming is to infer a program's output (posterior) distribution from a given initial (prior) distribution. This problem is cha…
Error Localization, Certificates, and Hints for Probabilistic Program Verification via Slicing (Extended Version)
Philipp Schröer, Darion Haase, Joost-Pieter Katoen
This paper focuses on effective user diagnostics generated during the deductive verification of probabilistic programs. Our key principle is based on providing slices for (1) error…
Exact Bayesian Inference for Loopy Probabilistic Programs using Generating Functions
Lutz Klinkenberg, Christian Blumenthal, Mingshuai Chen +2
We present an exact Bayesian inference method for inferring posterior distributions encoded by probabilistic programs featuring possibly unbounded loops. Our method is built on a d…