Several prediction approaches are contained in the arena of software engineering such as
prediction of effort, security, quality, fault, cost, and re-usability. All these prediction …

Since 2009, the deep learning revolution, which was triggered by the introduction of
ImageNet, has stimulated the synergy between Software Engineering (SE) and Machine …

Width deviation is an important metric for evaluating the quality of a hot-rolled strip in steel
production systems. This paper considers a width deviation prediction problem and …

This paper shows that the law, in subtle ways, may set hitherto unrecognized incentives for
the adoption of explainable machine learning applications. In doing so, we make two novel …

Software defect prediction aims to identify the potential defects of new software modules in
advance by constructing an effective prediction model. However, the model performance is …

Classifier specific (CS) and classifier agnostic (CA) feature importance methods are widely
used (often interchangeably) by prior studies to derive feature importance ranks from a …

Software defects are well-known in software development and might cause several
problems for users and developers aside. As a result, researches employed distinct …

Abstract Machine learning has proved to generate useful predictive models that can and
should support decision makers in many areas. The availability of tools for AutoML makes it …

Predictive models are one of the most important techniques that are widely applied in many
areas of software engineering. There have been a large number of primary studies that …

Context Interpretation has been considered as a key factor to apply defect prediction in
practice. As interpretation from rule-based interpretable models can provide insights about …