Software defect prediction is the process of locating defective modules in software. It
facilitates testing efficiency and consequently software quality. It enables a timely …

Background: Ensemble techniques have gained attention in various scientific fields. Defect
prediction researchers have investigated many state-of-the-art ensemble models and …

Recent advances in the domain of software defect prediction (SDP) include the integration of
multiple classification techniques to create an ensemble or hybrid approach. This technique …

Software defect prediction refers to the automatic identification of defective parts of software
through machine learning techniques. Ensemble learning has exhibited excellent prediction …

Software defect prediction is an active research area in software engineering. Accurate
prediction of software defects assists software engineers in guiding software quality …

Software defects are expensive in quality and cost. The accurate prediction of defect-prone
software modules can help direct test effort, reduce costs, and improve the quality of …

During the last 10 years, hundreds of different defect prediction models have been
published. The performance of the classifiers used in these models is reported to be similar …

Software defect prediction is one of the emerging research areas of software engineering.
The prediction of defects at early stage of development process can produce high quality …

Software defect prediction strives to improve software quality and testing efficiency by
constructing predictive classification models from code attributes to enable a timely …

Classification algorithms that help to identify software defects or faults play a crucial role in
software risk management. Experimental results have shown that ensemble of classifiers are …