Source-Code-Aware RAG for Autonomous Technical Documentation Generation - Sabuncu, Berkay; Turan, Said Hamza; Deǧer, Muhammed Şahver; Ayaz, Oǧuz; Baykara, Muhammet (Institute of Electrical and Electronics Engineers Inc., 2026)
The primary objective of this project is to develop a system that autonomously generates software architecture documentation after analyzing source code from GitHub repositories using a Retrieval-Augmented Generation (RAG) architecture and Large Language Models (LLMs). The developed system features a single architecture comprising a user-friendly interface (frontend), a server architecture (backend), a vector-based database, and IEEE-compliant DOCX output. This project offers a solution that automates the documentation and reporting processes, which are a significant burden for developers. © 2026 IEEE.
2nd International Symposium on AI-Driven Engineering Systems, ISADES 2026 -- 19 June 2026 through 20 June 2026 -- Hybrid, Mbale -- 226193
Keywords: Automated Documentation; Database; Llm; Rag; Source Code Analysis