How to Understand a New Codebase
You've been handed access to a repository with 50,000+ lines of code. No documentation. The original authors are gone. Where do you even start?
This guide will give you a systematic approach to understanding any codebase.
Quick Answer
Understanding a new codebase takes 2-4 weeks on average, but you can make meaningful contributions within 3-5 days using the right approach.
The Systematic Approach
Step 1: Get It Running (Day 1)
Before reading any code, get the application running locally.
# Clone and install
git clone <repo>
cd <repo>
npm install # or pip install, cargo build, etc.
# Run it
npm start
# Run tests
npm test
Why this matters: Running the app gives you concrete behavior to map back to code. Reading code without running it is like reading sheet music without hearing the song.
Step 2: Find the Entry Points (Day 1-2)
Every application has entry points—where execution begins:
| Type | Common Entry Points |
|---|---|
| Web app | index.html, App.js, main.tsx |
| Backend | main(), server.js, app.py |
| CLI | bin/, cli.js, __main__.py |
| Library | Exported functions in index.js or lib/ |
Start here and trace the flow forward.
Step 3: Identify Core Data Models (Day 2-3)
Find where the main entities are defined:
- Database schemas
- TypeScript interfaces
- Class definitions
- API response types
Understanding the data model is understanding half the system.
Step 4: Trace One Request End-to-End (Day 3-4)
Pick one user action and follow it through the entire system:
- User clicks button →
- Frontend handler →
- API call →
- Backend route →
- Business logic →
- Database query →
- Response →
- UI update
Document this flow. It's your map for understanding everything else.
Step 5: Map the Architecture (Week 1-2)
Create a mental (or actual) diagram of:
- Major components/modules
- How they communicate
- External dependencies
- Data flow
What to Look For
Folder Structure Patterns
src/
├── components/ # UI components
├── pages/ # Route handlers
├── services/ # Business logic
├── models/ # Data models
├── utils/ # Helpers
└── api/ # External integrations
Naming Conventions
- How are files named? (
UserService.tsvsuser-service.ts) - How are functions named? (
getUserByIdvsget_user_by_id) - What patterns do they follow? (Repository pattern? MVC? Hexagonal?)
Configuration Files
These reveal a lot about a project:
| File | Reveals |
|---|---|
package.json | Dependencies, scripts, project structure |
tsconfig.json | TypeScript setup, path aliases |
.env.example | Required environment variables |
docker-compose.yml | Services and infrastructure |
Makefile | Common operations |
Common Challenges
1. No Documentation
Solution: Use Ramp to generate documentation automatically:
ramp guide
This creates an ONBOARDING.md with architecture overview, key concepts, and common tasks.
2. Spaghetti Code
Solution: Focus on the happy path first. Ignore error handling, edge cases, and legacy code until you understand the core flow.
3. Missing Context
Solution: Use git log and git blame to understand why code was written:
# Who wrote this and why?
git blame src/auth/login.ts
# What changed recently?
git log --oneline -20
# What was the context for this change?
git show <commit-hash>
4. Unfamiliar Technology
Solution: Don't try to learn the framework AND the codebase simultaneously. Learn the framework basics first (30 minutes of tutorials), then return to the codebase.
Tools That Help
Ramp (Recommended)
# Voice-powered codebase exploration
ramp voice
> "How does authentication work in this codebase?"
> "Where are database migrations handled?"
> "What's the pattern for adding new API endpoints?"
Traditional Tools
- IDE search —
Cmd+Shift+Fto search across files - Call hierarchy — Right-click → "Find All References"
- Debugger — Set breakpoints and step through code
- Dependency graph —
madge(JS),pydeps(Python)
Timeline Expectations
| Experience Level | Basic Understanding | Full Productivity |
|---|---|---|
| Junior | 4-8 weeks | 3-6 months |
| Mid-level | 2-4 weeks | 1-3 months |
| Senior | 1-2 weeks | 2-4 weeks |
These can be cut in half with Ramp's AI-powered assistance.
Related Guides
Facing a new codebase? Try Ramp free →