Amaryllis is the first general-purpose probabilistic separation logic supporting dynamic memory allocation, independence, and conditioning, with a mechanized soundness proof in Rocq.
Bayesian Separation Logic: A Logical Foundation and Axiomatic Semantics for Probabilistic Programming
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Continuous-Eris is a new separation logic that verifies exact samplers for the uniform, Gaussian, and Laplace distributions plus an exact real arithmetic library, with all proofs machine-checked in Rocq.
Typed extended decision diagrams enable scalable deductive verification of probabilistic programs by compactly representing weakest pre-expectations.
Links noninterference to conditional independence so that probing security of masked algorithms can be checked inside the Lilac probabilistic separation logic.
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First Steps Towards Probabilistic Iris: Harmonizing Independence, Conditioning, and Dynamic Heap Allocation
Amaryllis is the first general-purpose probabilistic separation logic supporting dynamic memory allocation, independence, and conditioning, with a mechanized soundness proof in Rocq.