CONTEXT: Software metrics may be used in fault prediction models to improve software
quality by predicting fault location. OBJECTIVE: This paper aims to identify software metrics …

Software engineering discipline contains several prediction approaches such as test effort
prediction, correction cost prediction, fault prediction, reusability prediction, security …

Existing research is unclear on how to generate lessons learned for defect prediction and
effort estimation. Should we seek lessons that are global to multiple projects or just local to …

Software analytics builds quality prediction models for software projects. Experience shows
that (a) the more projects studied, the more varied are the conclusions; and (b) project …

Background: Code that is difficult to understand is also difficult to inspect and maintain and
ultimately causes increased costs. Therefore, it would be greatly beneficial to have source …

Data Science for Software Engineering: Sharing Data and Models presents guidance and
procedures for reusing data and models between projects to produce results that are useful …

Background. The extent of the potentially confounding effect of class size in the fault
prediction context is not clear, nor is the method to remove the potentially confounding effect …

Abstract Machine-learning techniques are used to find the defect, fault, ambiguity, and bad
smell to accomplish quality, maintainability, and reusability in software. Software fault …

Test resource constraints is a common phenomenon in software testing. Using defect
prediction to guide the resource allocation can significantly improve the efficiency and …

Assessing the quality of the software is both important and difficult. For this purpose,
software fault prediction (SFP) models have been extensively used. However, selecting the …