This project tackles code readability classification and bug localization in Python programs!
🔹 Code Readability: Using a Convolutional Neural Network (CNN) to predict how readable a Python snippet is.
🔹 Bug Localization: Leveraging pylint to identify and analyze potential issues in Python code.
By combining deep learning with static code analysis, this project helps developers write cleaner and more maintainable code! 🚀
🔹 Python
🔹 TensorFlow/Keras (for CNN Readability Model)
🔹 pylint (for Static Code Analysis)
🔹 Pandas & NumPy (for Data Processing)
🔹 Matplotlib/Seaborn (for Visualizations)
Step 1: Preprocess Python code snippets
Step 2: Train CNN to classify readability
Step 3: Use pylint to detect bugs and warnings
Step 4: Combine insights for better code improvement
Helps developers write readable code
Identifies bugs early
Provides data-driven insights into code quality