Bug Localization

Bug localization, the process of identifying the source code responsible for software errors, is a crucial step in software development, significantly reducing debugging time. Current research focuses on leveraging deep learning, particularly transformer-based models like LLMs, and reinforcement learning to improve the accuracy and efficiency of bug localization across different programming languages and projects. These advancements aim to address challenges like limited context windows and cross-project generalization, ultimately leading to more robust and reliable software systems. The development of comprehensive benchmark datasets and the exploration of techniques like domain adaptation are also key areas of ongoing investigation.