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Series
CodeAtlas is an AI-powered system that analyzes GitHub repos, generates AST-based insights, builds code relationship graphs, and helps developers understand complex projects through visualization and intelligent search.
Understanding a large or unfamiliar codebase is one of the hardest challenges for developers, students, and open-source contributors. Modern applications often span hundreds of files, multiple languages, and deeply intertwined module dependencies. Ma...
This week, I focused on two major milestones in the CodeAtlas project: implementing GitHub authentication and setting up monitoring for the key services. While I initially considered monitoring all services, I decided to start with a more practical a...
This week, I worked on something very important for CodeAtlas:👉 a logging system that is clean, stable, and easy to understand. At first, I tried many different methods.Some ideas worked, some failed, some broke the logs completely.But after testing...
This week was full of learning, confusion 😅, breakthroughs, and new features for CodeAtlas.I continued building on last week’s logging system and started working with GitHub APIs for the first time — which was not easy at all. Here’s everything I ac...
This week in CodeAtlas was all about building the repo_parser, normalizing ASTs, wrangling Neo4j graphs, and surviving Node.js quirks. Lots of learning, debugging loops, and small victories! 1. Repo Parser: Building the Core Route I started implemen...
This week in CodeAtlas was about moving from “it works” to “it survives real-world usage.” I focused on GitHub rate limits, backend graph exploration, logging, data integrity, and—most importantly—running a hard production readiness review that expos...
