Bridging Expert Knowledge with Deep Learning Techniques for Just-In-Time Defect Prediction

arXiv:2403.11079v1 Announce Type: cross
Abstract: Just-In-Time (JIT) defect prediction aims to automatically predict whether a commit is defective or not, and has been widely studied in recent years. In general, most studies can be classified into two categories: 1) simple models using traditional machine learning classifiers with hand-crafted features, and 2) complex models using deep learning techniques to automatically extract features from commit contents. Hand-crafted features used by simple models are based on expert knowledge but may not fully represent …

abstract arxiv classifiers cs.lg cs.se deep learning deep learning techniques expert features general jit knowledge machine machine learning prediction simple studies traditional machine learning type