LEDGE : Leveraging Dependency Graphs for Enhanced Context Aware Documentation Generation

This repository contains code, datasets, visualizations, and analysis for the research project, LEDGE : Leveraging Dependency Graphs for Enhanced Context Aware Documentation Generation. a novel framework that integrates dependency graphs with large language models (LLMs) to automate the generation of structured, context aware software documentation

Folder Structure

├── README.md
├── LICENSE
├── datasets/
│   ├── average_evaluation_results.csv
│   ├── evaluation_results.csv
│   └── quantitative_analysis.csv
├── diagrams/
└── notebooks/
    ├── evaluation.ipynb
    └── graphs.ipynb

Overview

Project Objective

LEDGE addresses the problem of incomplete or outdated documentation in large codebases. It does so by:

• Constructing dependency graphs from source code using custom parsers.
• Storing these graphs in MemGraph using Cypher queries for fast retrieval.
• Embedding code symbols for semantic similarity matching.
• Using a HybridRetriever that combines graph traversal and vector search to provide the LLM with rich context.
• Generating accurate, structured documentation with GraphRAG-based retrieval-augmented generation.

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Dataset

We evaluated LEDGE on five diverse open-source repositories:

Project	URL	Description
Next.js	https://github.com/vercel/next.js	React framework for server-side rendering
MobX	https://github.com/mobxjs/mobx	State management library
Turborepo	https://github.com/vercel/turborepo	Monorepo build system
Prisma	https://github.com/prisma/prisma	Type-safe database toolkit for TypeScript
Gatsby	https://github.com/gatsbyjs/gatsby	React-based static site generator

LEDGE outperforms traditional documentation in both qualitative and quantitative evaluations using metrics like BLEU, ROUGE-L, BERTScore, and Jaccard similarity.

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Notebooks

The notebooks/ folder includes interactive visualizations and reproducible analysis:

• evaluation.ipynb — Analyzes BLEU, ROUGE, and BERTScore comparisons between LEDGE and baseline documentation.
• graphs.ipynb — Plots for research paper.

These notebooks replicate core results from the paper and demonstrate the impact of graph-based retrieval in documentation generation.

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License

This project is licensed under the MIT License. See the LICENSE file for full details.

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BibTeX Entry and Citation Info

Please cite our paper:

@article{panchal2026ledge,
  title={LEDGE: Leveraging dependency graphs for enhanced context aware documentation generation},
  author={Panchal, Mihir and Deo, Arnav and Prabhu, Varad and Doshi, Prinkal and Bhadane, Chetashri and Bari, Pranit},
  journal={Automated Software Engineering},
  volume={33},
  number={2},
  pages={51},
  year={2026},
  publisher={Springer}
}

Contact

For questions, collaborations, or feedback, feel free to reach out:

Mihir Panchal – mihirpanchal5400@gmail.com
Arnav Deo – arnav.nitin.deo@gmail.com
Varad Prabhu – varadprabhu111@gmail.com
Prinkal Doshi – prinkaldoshi@gmail.com
Chetashri Bhadane – chetashri.bhadane@djsce.ac.in
Pranit Bari – pranit.bari@djsce.ac.in