This repository contains a pipeline for processing a modified version of the runbugrun dataset uploaded to HuggingFace, embedding buggy vs. fixed code pairs, and training a classifier to predict bug types.

TODO

TODO

• load_dataset.ipynb – Loads the runbugrun dataset, tokenizes buggy and fixed functions in chunks for later processing.
• EMBEDDER2.ipynb – Embeds the tokenized buggy–fixed pairs, computes the difference vectors between them, and saves these difference embeddings as files.
• classifier.ipynb – Uses the difference vectors to perform multi-label classification with hyperparameter search, predicting which bug labels correspond to each buggy function.

• Uses load_dataset.ipynb
• Tokenizes buggy and fixed functions in chunks.
• Prepares the data for embedding.

• Uses EMBEDDER2.ipynb
• Creates embeddings for each buggy and fixed function.
• Computes the difference vector (fixed - buggy) for each pair.
• Saves the difference vectors as files for later use.

• Uses classifier.ipynb
• Loads the saved difference vectors.
• Runs a hyperparameter search to find the best model setup.
• Trains a multi-label classifier to predict bug types (mapped to integers).