Advanced BE folder consist of

🚀 Real-time Code Execution System

A scalable, real-time online judge system inspired by LeetCode & Codeforces.

🌍 Overview

This system enables real-time code execution & problem-solving, where users submit code, it gets processed in a queue, executed by worker nodes, and results are delivered instantly via WebSockets.

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⚙️ System Architecture

🖥️ Client (Browser)

• Users submit code with:

  {
    "problem_id": 1,
    "code": "your_solution_here",
    "language": "java"
  }

• Sends the request to the Primary Backend.

🚀 Primary Backend

• Handles user submissions.
• Pushes execution requests into the Job Queue.

📌 Job Queue (Redis Queue)

• Stores execution requests in order.
• Ensures efficient processing with scalable workers.

🛠️ Worker Nodes (W1, W2, etc.)

• Fetch jobs from the queue.
• Execute code in an isolated environment.
• Return execution results (e.g., ✅ Accepted, ❌ Time Limit Exceeded).

📡 WebSocket Server

• Listens for execution results from workers.
• Sends real-time updates back to users.

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🔄 Flow Diagram

📌 Step-by-step execution flow:
1️⃣ User submits code in the browser.
2️⃣ The backend pushes the job into the queue.
3️⃣ Workers fetch jobs and execute them securely.
4️⃣ Results are sent to WebSocket, then to the user.

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🛠️ Tech Stack

Component	Technology Used
🌐 Backend	Node.js + Express
🔄 Queue	Redis (Pub/Sub + Job Queue)
📡 Real-time	WebSockets (ws)
🖥️ Execution	Worker Nodes (Docker/Sandboxed Env)

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🚀 Key Features

✅ Real-time code execution 🕒
✅ Scalable worker-based processing 🔥
✅ WebSocket-based live updates 📡
✅ Queue-based execution system 📌
✅ Multi-language support (Java, Python, C++, etc.) 🛠️

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📌 Future Improvements

• 🔹 Scalability: Auto-scaling workers with Kubernetes.
• 🔹 Caching: Store results for common test cases.
• 🔹 Security: Isolated execution for preventing malicious code.

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💡 Inspired by competitive coding platforms like LeetCode & Codeforces.
💻 Built for efficiency, scalability & real-time feedback.

🚀 Let’s code & optimize!

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