mlsanityData to 7 Oct 2026

CODENS: Transforming Code Changes into Living, Accessible, and Queryable Documentation

arXiv 2607.18356 ↗First posted 20 Jul 2026cs.SE cs.AIcited by 1

Not on the map. Why?

Abstract (arXiv)

Maintaining up-to-date code documentation is difficult in fast-moving repositories because design knowledge is scattered across source files and pull requests. We present CODENS , a system that turns pull requests into living, accessible, and queryable documentation for production codebases. CODENS incrementally builds a typed software knowledge graph from pull requests, enriches components through schema-driven semantic extraction, derives typed relations between them, and exposes the resulting knowledge through three retrieval modes, including agent-guided graph traversal for repository-level question answering. The system also preserves semantic change history across pull requests and integrates both answer-quality and operational evaluation metrics. We evaluate CODENS on a client Ruby on Rails project in production. Results show that CODENS produces highly relevant and well-grounded answers, while qualitative feedback highlights a remaining challenge in concise, documentation-oriented synthesis.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 4 of its 10 references that are in the map. First posted on arXiv 20 Jul 2026.

Builds on

4 of 10 references.

References · 4

  1. 2024From Local to Global: A Graph RAG Approach to Query-Focused Summarizationcited by 1,411
  2. 2021CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generationcited by 890
  3. 2023RepoCoder: Repository-Level Code Completion Through Iterative Retrieval and Generationcited by 357
  4. 2024CodexGraph: Bridging Large Language Models and Code Repositories via Code Graph Databasescited by 62

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.