Software fault prediction aims to identify fault-prone software modules by using some
underlying properties of the software project before the actual testing process begins. It …

Abstract Context: Defect Number Prediction (DNP) models can offer more benefits than
classification-based defect prediction. Recently, many researchers proposed to employ …

Software systems have become larger and more complex than ever. Such characteristics
make it very challengeable to prevent software defects. Therefore, automatically predicting …

Modern society is increasingly moving toward complex and distributed computing systems.
The increase in scale and complexity of these systems challenges O&M teams that perform …

Context Software defect prediction (SDP) plays an important role in allocating testing
resources reasonably, reducing testing costs, and ensuring software quality. However …

Context Software defect prediction strives to detect defect-prone software modules by mining
the historical data. Effective prediction enables reasonable testing resource allocation …

Background. Solving the class-imbalance problem of within-project software defect
prediction (SDP) is an important research topic. Although some class-imbalance learning …

In Continuous Integration (CI), regression testing is constrained by the time between
commits. This demands for careful selection and/or prioritization of test cases within test …

Abstract Support Vector Machine (SVM) has been widely used to build software defect
prediction models. Prior studies compared the accuracy of SVM to other machine learning …

Sorting software modules in order of defect count can help testers to focus on software
modules with more defects. One of the most popular methods for sorting modules is …