Survey on Learning-based Dynamic Fault Localization: From Traditional Machine Learning to Large Language Models

This survey examines methods for automatically finding bugs in software code by using machine learning and AI models, tracing the evolution from traditional machine learning techniques to modern large language models (LLMs, which are AI systems trained on vast amounts of text data). The research covers how these AI-based approaches learn patterns to pinpoint where faults occur in code, making debugging faster and more efficient than manual inspection.