LIP

Learning-based automatic program repair uses machine learning to build models that generate patches for programs to be fixed. It is highly automatic and is not tied to a particular application setting. With large corpora of repairs and strong neural results on code tasks, learning-based methods — especially those based on neural machine translation (NMT-based automatic program repair, also called neural program repair, NPR) — have become an emerging direction in automatic program repair.