Automated Program Repair using Large Language Models (LLMs)
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Date
2025-06-15
Journal Title
Journal ISSN
Volume Title
Publisher
Mohamed Boudiaf University of M'sila
Abstract
This work proposes an approach to APR by integrating a fine-tuned CodeLLaMA-7b model
with a GraphRAG-based retrieval framework. We first applied LoRA to fine-tune the
CodeLLaMA model using the domain-specific RepairLLaMA dataset. To enhance contextual
awareness, we built a graph-based retriever that combines CodeBERT-generated embeddings
with structural relationships between buggy and fixed code pairs from the Defects4J dataset.
Our system prioritizes relevant repair examples and enables efficient retrieval of code context.
Additionally, we developed a simple web interface to provide real-time bug fix suggestions,
demonstrating the practical applicability of our pipeline.
Description
Keywords
Large Language Models, Automated Program Repair, GraphRAG, Fine-tuning