🗺️ CodeMap

See the architecture. Skip the chaos.

An automated, interactive map of any large codebase — built to make developer onboarding 10× faster.

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📌 Table of Contents

• The Problem
• Our Solution
• Key Features
• Run Locally
• How It Works
• Tech Stack
• Measurable Impact
• Challenges & Learnings
• Roadmap
• Team

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🚀 Run Locally

1) Frontend

npm install
copy .env.example .env
npm run dev

Frontend runs on http://localhost:5173.

2) Backend

cd backend
npm install
copy .env.example .env
npm run dev

Backend runs on http://localhost:3001 and exposes:

• POST /api/analyze
• GET /api/graph/:graphId
• GET /api/summary/:fileId
• GET /api/onboarding/:graphId
• POST /api/query
• GET /api/health

Optional: set GROQ_API_KEY in backend/.env for AI summaries and chat.

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🚨 The Problem

Onboarding new engineers to large codebases is broken at scale.

Metric	Reality
⏳ Time to productivity	3–9 months for a new engineer on a large codebase (Stripe Developer Coefficient Report)
💸 Annual cost	$85 Billion lost to onboarding inefficiency across the tech industry
🧑‍💼 Senior engineer drain	40% of a senior engineer's week spent answering newcomer questions
📖 Dev time wasted	60% of a new dev's time spent reading code instead of building

Where It Hurts Most

• Tracing imports for weeks — newcomers manually trace dependencies across hundreds of files just to understand a single feature.
• Senior engineers as oracles — tribal knowledge lives in heads, not docs. Constant interruptions kill team velocity.
• Docs are stale or missing — README files lie. Architecture diagrams rot. The code is the only source of truth — but it's unreadable at scale.
• No structural map exists — IDEs show files. Git shows commits. Nothing shows how the system actually fits together.

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💡 Our Solution

CodeMap is a tool that reads your codebase and renders the true, living architecture — automatically.

PARSE  →  MAP  →  VISUALIZE

Stage	What Happens
I — Parse	AST-level analysis of every file, function, class, import & call across the repo
II — Map	Build a typed dependency graph showing real relationships — not just folder structure
III — Visualize	Interactive 2D/3D graph + AI summaries. Zoom from system → module → function

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✨ Key Features

Feature	Description
🔍 Auto-Architecture Extraction	Zero config. Point at a repo — get a complete structural map in minutes
🤖 AI-Powered Assistant	Fully functional AI services that enhance the learning and exploration experience
🌐 Multi-Language Support	Python, TypeScript, JS, Java, Go — one unified graph across polyglot codebases
🖱️ Interactive Exploration	Pan, zoom, filter, search. Click a node → see callers, callees, and dependents instantly
🧭 Onboarding Tours	Auto-generated guided walkthroughs of "how a request flows" or "where auth lives"
🔄 Continuous Sync	Re-indexes on every commit. The map never goes stale

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⚙️ How It Works

┌─────────┐    ┌─────────┐    ┌─────────┐    ┌─────────┐    ┌─────────┐
│  INGEST │ →  │  PARSE  │ →  │  GRAPH  │ →  │  ENRICH │ →  │  RENDER │
│         │    │         │    │         │    │         │    │         │
│ Clone   │    │Tree-    │    │ Nodes = │    │ AI      │    │ D3 /    │
│ repo or │    │sitter   │    │ files,  │    │summaries│    │Three.js │
│ connect │    │ ASTs,   │    │ edges = │    │via LLM  │    │interactive│
│ GitHub  │    │multi-   │    │imports/ │    │gateway  │    │  view   │
│         │    │language │    │  calls  │    │         │    │         │
└─────────┘    └─────────┘    └─────────┘    └─────────┘    └─────────┘

Output → A live, 3D-queryable architecture map. New devs explore visually instead of reading 10,000 files.

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🛠️ Tech Stack

Frontend

Backend

Parsing & Analysis

• Tree-sitter (AST traversal)
• LSP Servers
• Custom Analyzers

AI / LLM

• Lovable AI Gateway
• Embeddings
• RAG Pipeline

Data & Storage

Infrastructure

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📊 Measurable Impact

Metric	Impact
⚡ Time-to-first-PR for new devs	10× Faster
🤫 Senior engineer interruption time	70% Less
🚀 Setup time (repo URL → interactive map)	< 5 Minutes
🗂️ Codebase coverage	100% — every file, every dependency

"Imagine joining a 2-million-line codebase on Monday and shipping a real fix by Friday. That's what CodeMap unlocks."

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🧠 Challenges & Learnings

1. Scaling the Parser to Millions of Lines of Code

• Problem: Naive AST walks ran out of memory on real-world repos.
• Solution: Streaming parser + incremental graph builder, sharded by module.

2. Cross-Language Dependency Resolution

• Problem: Imports look different in every language; symbols cross boundaries.
• Solution: Unified IR layer that normalizes Python, TypeScript, Go, and Java into one graph schema.

3. Making the Visualization Actually Useful

• Problem: A 10,000-node graph is just visual noise — worse than no map.
• Solution: Hierarchical clustering + on-demand expansion + AI-driven focus modes.

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🗓️ Roadmap

NOW (MVP)              Q2 2026               Q3 2026               2027 Vision
─────────────          ─────────────         ─────────────         ─────────────
✅ Multi-lang parser   🔲 VS Code extension  🔲 Onboarding tours   🔲 Auto-refactor
✅ Interactive 3D graph 🔲 GitHub integration 🔲 Slack bot           🔲 Cross-repo intel
✅ AI services         🔲 Team workspaces    🔲 Drift alerts        🔲 Enterprise on-prem

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👥 Team

Team BugSlayers — Hackathon 2026, Problem Statement #03

Built with 💙 to make every developer's first week their best week.

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⭐ Star this repo if you believe onboarding shouldn't take months.