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LOC: ~3,610
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Languages: Rust, Julia, Idris2, Zig
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Existing ABI proofs:
src/abi/*.idr(template-level) -
Dangerous patterns: None detected
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contrastive_model.jl,julia_utils.jl— data processing pipeline -
Prove: normalization is invertible (or document when it is lossy)
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Prove: contrastive model training preserves dataset statistical properties
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Dataset metadata management
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Prove: metadata correctly describes the normalized dataset
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Lean4 with Mathlib for numerical/statistical properties
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Idris2 for ABI layer and metadata invariants
LOW — Dataset preprocessing tool. Normalization correctness matters for ML pipeline reproducibility but is not safety-critical. The small codebase limits the scope of potential errors.