Recent years have experienced sustained focus in research on software defect prediction
that aims to predict the likelihood of software defects. Moreover, with the increased interest …

Software Vulnerability Prediction (SVP) is a data-driven technique for software quality
assurance that has recently gained considerable attention in the Software Engineering …

The use of learning-based techniques to achieve automated software vulnerability detection
has been of longstanding interest within the software security domain. These data-driven …

Software defect prediction, which predicts defective code regions, can assist developers in
finding bugs and prioritizing their testing efforts. Traditional defect prediction features often …

Existing work on software patches often use features specific to a single task. These works
often rely on manually identified features, and human effort is required to identify these …

Software quality assurance efforts often focus on identifying defective code. To find likely
defective code early, change-level defect prediction-aka. Just-In-Time (JIT) defect prediction …

A Just-In-Time (JIT) defect prediction model is a classifier to predict if a commit is defect-
introducing. Recently, CC2Vec-a deep learning approach for Just-In-Time defect prediction …

Pre-trained models like BERT have achieved strong improvements on many natural
language processing (NLP) tasks, showing their great generalizability. The success of pre …

Software defect prediction is one of the most active fields in software engineering. Recently,
some experts have proposed the Just-in-time Defect Prediction Technology. Just-in-time …

Defect prediction aims to automatically identify potential defective code with minimal human
intervention and has been widely studied in the literature. Just-in-Time (JIT) defect prediction …