🔍 Dead Code Detector

AI-Powered Static Analysis Tool for Python & JavaScript

Detect unused functions, dead variables, and unreachable code blocks across your entire codebase — with AI-powered explanations and fix suggestions.

Features • Tech Stack • Setup • Usage • API Docs

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🚀 What is Dead Code Detector?

Dead Code Detector is a full-stack AI-powered static analysis tool that goes beyond simple linting. It parses your code into an Abstract Syntax Tree (AST), builds a cross-file call graph, and uses a Large Language Model (LLM) to explain why each piece of code is dead and how to fix it.

Unlike basic linters, this tool:

• Analyzes multiple files together — a function used in main.py but defined in utils.py is correctly identified as alive
• Uses AI to explain dead code in plain English, not just flag line numbers
• Visualizes your entire function call graph interactively
• Provides real-time analysis as you type via WebSocket

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✨ Features

Feature	Description
🧠 AI Explanations	Groq LLaMA3 explains why each dead code block exists and how to fix it
🌐 Cross-File Analysis	Upload entire projects — detects functions unused across ALL files
📊 Interactive Call Graph	Force-directed graph showing function relationships with dead nodes highlighted in red
⚡ Live WebSocket Analysis	Real-time dead code detection as you type in the editor
🎨 Monaco Editor	VS Code's editor embedded in the browser with syntax highlighting
📄 PDF Export	Generate professional dark-themed reports with AI explanations
🐍 Multi-Language	Full support for Python and JavaScript/TypeScript
📁 File Upload	Upload single files or entire project folders
💊 Health Score	Codebase health percentage based on dead code ratio

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🛠️ Tech Stack

Backend

Technology	Purpose
FastAPI	High-performance REST API and WebSocket server
Python AST	Built-in Python abstract syntax tree parser
Esprima	JavaScript AST parser for JS/TS analysis
Groq (LLaMA 3.3-70B)	Free LLM API for AI-powered code explanations
Uvicorn	ASGI server for async request handling
WebSockets	Real-time bidirectional communication

Frontend

Technology	Purpose
React 18	Component-based UI framework
Vite	Lightning-fast build tool and dev server
Monaco Editor	VS Code's editor for in-browser code editing
Cytoscape.js	Interactive call graph visualization
Axios	HTTP client for API communication
jsPDF	Client-side PDF generation
Lucide React	Modern icon library

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📁 Project Structure

dead-code-detector/
├── backend/
│   ├── app/
│   │   ├── analyzers/
│   │   │   ├── ast_analyzer.py        # Python & JS AST analysis
│   │   │   ├── llm_analyzer.py        # Groq LLM integration
│   │   │   ├── call_graph.py          # Call graph builder
│   │   │   └── cross_file_analyzer.py # Multi-file analysis engine
│   │   ├── routers/
│   │   │   ├── analyze.py             # REST API endpoints
│   │   │   └── websocket.py           # WebSocket endpoint
│   │   └── main.py                    # FastAPI app entry point
│   ├── .env                           # Environment variables (not committed)
│   ├── .env.example                   # Example environment file
│   └── requirements.txt               # Python dependencies
│
├── frontend/
│   ├── src/
│   │   ├── App.jsx                    # Main React component
│   │   ├── main.jsx                   # React entry point
│   │   └── index.css                  # Global dark theme styles
│   ├── package.json
│   └── vite.config.js
│
└── README.md

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⚙️ Setup

Prerequisites

• Python 3.10+
• Node.js 18+
• A free Groq API key

1. Clone the repository

git clone https://github.com/manishaagangadevi/dead-code-detector.git
cd dead-code-detector

2. Backend Setup

# Navigate to backend
cd backend

# Create virtual environment
python -m venv venv

# Activate virtual environment
# Windows:
venv\Scripts\activate
# Mac/Linux:
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Create .env file
cp .env.example .env

# Add your Groq API key to .env
# GROQ_API_KEY=your_key_here

# Start the backend server
uvicorn app.main:app --reload

Backend will run at: http://127.0.0.1:8000

3. Frontend Setup

# Open new terminal, navigate to frontend
cd frontend

# Install dependencies
npm install

# Start development server
npm run dev

Frontend will run at: http://localhost:5173

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📖 Usage

Single File Analysis

1. Open http://localhost:5173
2. Paste your Python or JavaScript code in the editor
3. Select the language from the dropdown
4. Click Analyze
5. View issues, call graph, and AI explanations in the right panel

Multi-File Project Analysis

1. Click Upload Project button
2. Select multiple .py or .js files from your project
3. Click Analyze
4. The tool will analyze all files together — functions used across files are correctly identified as alive

Export Report

After analysis, click Export PDF to download a detailed dark-themed report including:

• Summary statistics
• All dead code issues with line numbers
• AI explanations for each issue
• Fix suggestions

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🔌 API Reference

POST /api/analyze

Analyze a single file for dead code.

Request:

{
  "code": "def unused_func():\n    pass\n",
  "language": "python"
}

Response:

{
  "success": true,
  "language": "python",
  "total_lines": 2,
  "dead_count": 1,
  "dead_code_items": [
    {
      "type": "dead_function",
      "name": "unused_func",
      "line_start": 1,
      "line_end": 2,
      "severity": "high",
      "message": "Function 'unused_func' is defined but never called",
      "ai_explanation": "...",
      "fix_suggestion": "..."
    }
  ],
  "call_graph": { "nodes": [], "edges": [] },
  "summary": {
    "dead_functions": 1,
    "dead_variables": 0,
    "unreachable_blocks": 0
  }
}

POST /api/analyze-project

Analyze multiple files together with cross-file awareness.

Request:

{
  "files": [
    { "filename": "main.py", "code": "..." },
    { "filename": "utils.py", "code": "..." }
  ],
  "language": "python"
}

GET /api/health

Health check endpoint.

WS /ws/analyze

WebSocket endpoint for real-time analysis. Send JSON:

{ "code": "...", "language": "python" }

Full interactive API documentation available at http://127.0.0.1:8000/docs

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🧠 How It Works

Code Input
    │
    ▼
AST Parser (Python AST / Esprima)
    │
    ▼
Symbol Table Builder
├── Collect all defined functions
├── Collect all defined variables
└── Collect all function calls & usages
    │
    ▼
Cross-File Reference Resolver
├── Build global symbol table across all files
├── Resolve imports and exports
└── Mark functions used in any file as alive
    │
    ▼
Dead Code Detector
├── Functions defined but never called = dead
├── Variables assigned but never used = dead
└── Code after return statements = unreachable
    │
    ▼
LLM Analyzer (Groq LLaMA 3.3-70B)
├── Explain why each block is dead
└── Suggest specific fixes
    │
    ▼
Call Graph Builder
└── Visualize function relationships
    │
    ▼
Results (UI + PDF Export)

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🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the project
2. Create your feature branch (git checkout -b feat/amazing-feature)
3. Commit your changes (git commit -m 'feat: Add amazing feature')
4. Push to the branch (git push origin feat/amazing-feature)
5. Open a Pull Request

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👩‍💻 Author

Manisha Gangadevi

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Made with ❤️ for the love of clean code

⭐ Star this repo if you found it helpful!