🐞 AI Code Debugger

A lightweight AI-based code debugging and static analysis tool that analyzes Python source code, detects common issues, and provides useful suggestions to improve code quality.

📌 Overview

AI Code Debugger is a command-line application designed to help developers identify common Python coding problems without manually checking every line.

The application uses Python's built-in ast module to validate Python syntax and performs additional static checks on the source code.

It is simple, beginner-friendly, and can be extended with AI/LLM capabilities in the future.

✨ Features

• 🔍 Detects code syntax errors
• 🧠 Performs basic static code analysis
• 📏 Detects unnecessarily long lines
• ⚠️ Identifies possible unintended comparison usage
• 🐛 Detects debug print() statements
• 💡 Provides suggestions for fixing detected issues
• 💻 Simple command-line interface
• 🚀 Easy to run and extend

🛠️ Technologies Used

• OPEN AI
• AST (Abstract Syntax Tree)
• Command Line Interface (CLI)

📂 Project Structure

AI-Code-Debugger/
│
├── app.py
├── requirements.txt
├── README.md
└── .gitignore

app.py

Contains the main debugging and static-analysis logic.

requirements.txt

Contains project dependencies.

This project currently uses Python's built-in ast module, so no external Python packages are required.

README.md

Contains project documentation and instructions for running the application.

⚙️ How It Works

The application follows these steps:

User enters Python code
        ↓
Code is collected through CLI
        ↓
Python AST syntax validation
        ↓
Static code analysis
        ↓
Issues are detected
        ↓
Suggestions are generated
        ↓
Analysis report is displayed

🚀 Installation

1. Clone the repository

git clone https://github.com/YOUR-USERNAME/AI-Code-Debugger.git

2. Navigate to the project

cd AI-Code-Debugger

3. Create a virtual environment

Windows:

python -m venv venv
venv\Scripts\activate

Linux/macOS:

python3 -m venv venv
source venv/bin/activate

4. Install dependencies

pip install -r requirements.txt

Since the project currently uses only Python's standard library, there are no external dependencies.

▶️ Running the Application

Run:

python app.py

You will see:

=== AI Code Debugger ===
Paste your Python code. Type END on a new line to finish.

Enter your Python code and type:

END

when you are finished.

🧪 Example

Input

def calculate_sum(a, b)
    print(a + b)

calculate_sum(10, 20)
END

Output

--- Analysis Report ---

Issues Found:
- Syntax Error: expected ':'

Suggestions:
- Check the reported line and fix syntax issues.

🔎 Example of Static Analysis

Input:

x = 10

if x == 10:
    print("Debugging")

The debugger can provide suggestions such as:

Suggestions:
- Line 4: Remove debug print statements before production deployment.

🎯 Use Cases

This project can be useful for:

• Python beginners learning debugging
• Students practicing programming
• Identifying simple syntax errors
• Basic static code analysis
• Learning how AST-based analysis works
• Building a foundation for an AI-powered coding assistant

🔮 Future Improvements

The project can be extended with:

• 🤖 OpenAI/LLM-based code explanations
• 🔧 Automatic code correction
• 📊 Code quality scoring
• 🖥️ Web interface using Streamlit or Flask
• 📁 Upload Python files for analysis
• 📝 Detailed error explanations
• 🔍 More advanced static analysis rules
• 💬 Natural-language debugging assistance
• 🧪 Automated test generation
• 🔐 Secure sandboxed code execution

🤝 Contributing

Contributions are welcome.

1. Fork the repository
2. Create a new branch
3. Make your changes
4. Commit your changes
5. Push your branch
6. Create a Pull Request

📄 License

This project is open-source and available under the MIT License.

👨‍💻 Author

Jetty Usha Rani

Computer Science Student
Mohan Babu University

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