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AWS open-sources anti-unification policy semantic diff engine

1 reports1 sources3 days agoUpdated

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The AWS Machine Learning Blog introduced an open-source engine that uses anti-unification on e-graphs to compute the most specific common pattern of two formal policies: identical parts are shown only once, and differing parts retain both versions for review. The engine does not directly import native policies from Cedar, Dogwood, OpenShell, or CEL; instead, it encodes the relevant syntax as terms and declares equalities, and is mainly used to compare multiple candidates generated by LLM autoformalization. The engine is released on GitHub under the Apache-2.0 license, and building from source only requires a pinned version of the Rust toolchain. AWS says that if a difference is not eliminated, it may simply be that the engine has not yet discovered the corresponding equivalence.

AI overview based on source reports · Updated 3 days ago

Latest developmentNov 12 07:33
Semantic diff of formal policies using anti-unification

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Nov 12
  1. AWS Machine Learning Blog
    Semantic diffing of formal policies with anti-unification

    The post describes an open source engine that computes semantic diffs of formal policies by anti-unification over an e-graph, using declared algebraic laws and domain rewrites so that shared structure appears once and each genuine disagreement is kept as a Variants node. Worked examples cover SMT-LIB-style rules, Cedar and Dogwood authorization policies, and OpenShell and CEL encodings, showing how presentational differences are absorbed while real bugs such as a weakened conjunction or a dropped guard remain visible. The engine builds from source with a pinned Rust toolchain and reads a single S-expression file.

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