AutoJudge: Predicting Programming Problem Difficulty

📌 Project Overview

AutoJudge is a machine learning–based system that automatically predicts the difficulty level of programming problems using only their textual descriptions. The system performs two tasks:

1. Classification: Predicts the difficulty class

        → Easy / Medium / Hard
   

2. Regression: Predicts a numerical difficulty score

The prediction is based solely on problem text (description, input, output), without using user submissions or platform statistics. A Streamlit web interface is provided for real-time inference on new problem statements.

⚙️ Installation & Setup

1. Clone the Repository

   git clone<repository-url>
   cd AutoJudge

2. Install Dependencies

   pip install pandas numpy scikit-learn joblib streamlit

Running the Project

Step 1 : Train the models (acm_classifier.ipynb)

This Step:

1. Loads dataset
2. Trains classification & regression models
3. Evaluates performance
4. Saves trained models

Step 2 : Launch Web Application

This web app loads the saved models and performs inference only

Run this in the Command Prompt and make sure the working directory is the same as the cloned file.

streamlit run app.py

Web Interface Usage

1. Paste:

   a) Problem Description

   b) Input Description

   c) Output Description

2. Click Predict Difficulty

3. View:

   a) Predicted Difficulty Class

   b) Predicted Difficulty Score

⚠️ Note: The numerical difficulty score corresponds to the scale present in the training dataset and does not represent platform-specific ratings such as Codeforces scores.

To View the Demo Video Download it to watch it fully or use the link:

https://drive.google.com/file/d/16NXo2LxZjWUUCvy6zbNXxfw_kptE87US/view?usp=sharing