Show HN: Lean4 Datalog DSL Based on Google Zanzibar for AI Projects
A new Lean4 Datalog domain-specific language (DSL) called ZIL has been introduced to help manage project relationships and requirements. Inspired by Google's Zanzibar authorization system, it allows developers to query complex dependencies and project metadata.
Why it matters
This tool offers a structured way for AI assistants and developers to maintain consistency and traceability in large-scale software projects.
ZIL is a small relational language for describing named objects, the relationships between them, and rules that derive additional relationships.
subject ── relation ──▶ object For example:
lean.Parser.parse ── implements ──▶ requirement.parseInput ZIL Lean implements this model inside Lean 4. Lean checks definitions, executable programs, theorem statements, and proofs. ZIL records how those checked declarations relate to requirements, documents, tests, tasks, dependencies, and other parts of a project.
The same project map can answer questions such as:
which declaration implements this requirement? which theorem validates this component? which modules depend on this declaration? which task is waiting for this result? which declarations should be reviewed after this change? Developers, review tools, CI, documentation tools, and AI assistants can query the same stored relationships.
ZIL's relation model is influenced by the tuple-oriented model described in Google's Zanzibar paper:
Zanzibar: Google's Consistent, Global Authorization System (USENIX ATC '19)
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