🧼 Code Smell Detector Web App

A powerful refactoring assistant that detects code smells and suggests intelligent improvements using LLMs (Large Language Models). Built for developers, this web-based tool includes a live coding IDE, multi-language support, and seamless AI integration — helping you write cleaner code, faster.

🚀 Created using modern web technologies, AI models, and AWS cloud services.

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📸 Demo Preview

✨ Example: Python code analysis detecting a Long Parameter List and Primitive Obsession code smell using LLM evaluation.

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🌟 Features

• 💻 Web IDE: Paste code directly in the browser.
• 🧠 Multi-LLM Evaluation: Analyzes code using multiple large language models.
• 🌐 Multi-language Detection: Supports Python, JavaScript, Java, and more.
• 🔍 Refactoring Suggestions: Get practical, explainable tips to improve code quality.
• 🛠️ Built for Developers: IDE-style experience with language selection.
• ☁️ Scalable Cloud Deployment: AWS-ready architecture.
• 🧠 Powered by Python 3.11 for backend AI analysis.

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🧰 Tech Stack

🎨 Frontend

• Next.js
• (optional for styling)

⚙️ Backend

• Node.js
• Express.js
• Python 3.11 (LLM Evaluation Microservice)

🛢️ Database

• MongoDB

☁️ Deployment (Tested on AWS)

• Amplify – Frontend hosting
• ECS – Container orchestration
• ECR – Docker image storage
• API Gateway – API routing

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🖼 Screenshot Example

📌 The example above shows a Python function create_user_profile passed into the tool:

• Detected Long Parameter List smell with 8 parameters
• Detected Primitive Obsession (relying on primitive types)
• Models recommended grouping data into a class like UserProfile

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🧪 How to Run Locally

🔧 Prerequisites

• Node.js (v18+)
• Python 3.11+
• MongoDB
• Docker (optional for container setup)

📦 Install Frontend

cd frontend
npm install
npm run dev

cd backend
npm install
node index.js


🛣 Roadmap
 More language support (Go, Rust, C++)

 OAuth login (GitHub or Google)

 User history dashboard

 Upload full files / drag-and-drop

 In-browser refactor preview

🧑‍💻 Author
Huy Quoc Nguyen



⚠️ Deployment Notes
💸 Full deployment was tested on AWS but paused to prevent excessive costs.

📄 License
MIT License – free for personal and educational use.