Delivering high-quality software products is a challenging task. It needs proper coordination
from various teams in planning, execution, and testing. Many software products have high …

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 …

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 …

Throughout its development period, a software project experiences different phases,
comprises modules with different complexities and is touched by many different developers …

Just-In-Time Software Defect Prediction (JIT-SDP) is concerned with predicting whether
software changes are defect-inducing or clean based on machine learning classifiers …

Context Software defect prediction is an important technique that can help practitioners
allocate their quality assurance efforts. In recent years, just-in-time (JIT) defect prediction has …

Abstract Unsupervised Effort-Aware Defect P rediction (EADP) uses unlabeled data to
construct a model and ranks software modules according to the software feature values. Xu …

Predicting defect-prone software components can play a significant role in allocating
relevant testing resources to fault-prone modules and hence increasing the business value …

Cross-Project (CP) Just-In-Time Software Defect Prediction (JIT-SDP) makes use of CP data
to overcome the lack of data necessary to train well performing JIT-SDP classifiers at the …

Software defect prediction studies aim to predict defect-prone components before the testing
stage of the software development process. The main benefit of these prediction models is …