{
  "title": "COGANT: Deterministic Codebase-to-GNN Translation",
  "version": "0.6.0",
  "doi": "10.5281/zenodo.20705351",
  "doi_url": "https://doi.org/10.5281/zenodo.20705351",
  "concept_doi": "10.5281/zenodo.20705350",
  "zenodo_record": "https://zenodo.org/records/20705351",
  "record_id": "20705351",
  "publication_date": "2026-06-15",
  "resource_type": {
    "title": "Journal article",
    "type": "publication",
    "subtype": "article"
  },
  "license": "MIT",
  "creators": [
    {
      "name": "Friedman, Daniel Ari",
      "affiliation": "Active Inference Institute",
      "orcid": "0000-0001-6232-9096"
    }
  ],
  "description": "COGANT (Codebase-to-GNN Translation) deterministically converts software repositories into structured Active Inference artifacts expressed in the Active Inference Institute's Generalized Notation Notation (GNN - Generalized Notation Notation, not graph neural networks). It is an evidence compiler: it propagates reviewable program facts through a fixpoint rule pipeline and emits graph, matrix, provenance, visualization, and roundtrip artifacts rather than a single opaque embedding or proof. A program-graph intermediate representation (IR) carries confidence and provenance; a fixpoint translation engine applies 22 declarative rules mapping nodes onto 7 Active Inference mapping kinds. Each emitted bundle includes a seed-induced structural partition using Markov-blanket role vocabulary, and a reverse synthesizer reconstructs a runnable Python package from an emitted GNN bundle, closing a forward-reverse-forward evaluation loop. The v0.6.0 release reports 9,697 passing tests, 95.55% line coverage, and a 25-target round-trip regression corpus. Dual Python/Rust architecture; MIT-licensed. Code home: https://github.com/ActiveInferenceInstitute/COGANT.",
  "keywords": [
    "program analysis",
    "Generalized Notation Notation",
    "GNN",
    "intermediate representation",
    "code property graph",
    "active inference",
    "reproducible research",
    "codebase-to-model translation",
    "cognitive ecosystem modeling"
  ],
  "files": [
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      "checksum": "md5:dedaed9bedb1243962e9a462a38e47fc",
      "download_url": "https://zenodo.org/api/records/20705351/files/COGANT-0.6.0.pdf/content"
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  "related_resources": [
    {
      "relation": "isSupplementedBy",
      "identifier": "https://github.com/ActiveInferenceInstitute/COGANT",
      "type": "software"
    }
  ],
  "github_repo": "https://github.com/ActiveInferenceInstitute/COGANT",
  "source": "zenodo-with-github",
  "checked_at": "2026-06-15T18:00:00Z"
}