Semantic diffing with anti-unification compares formal policies by meaning, not text
AIAWS Machine Learning Blog describes a semantic diff for formal policies that uses anti-unification over an e-graph to show shared structure and where two translations differ. The engine takes SMT-LIB, Cedar, Dogwood, OpenShell, or CEL policy encodings, with algebraic laws and domain rules supplied to justify equalities.
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AWS Machine Learning Blog · Ferhat Erata · aws.amazon.comPublished · added here
Original title: Semantic diffing of formal policies with anti-unification