Context: There is considerable diversity in the range and design of computational
experiments to assess classifiers for software defect prediction. This is particularly so …

Software fault prediction (SFP) aims to improve software quality with a possible minimum
cost and time. Various machine learning models have been proposed in the past for …

Context: Software engineering researchers have undertaken many experiments
investigating the potential of software defect prediction algorithms. Unfortunately some …

Numerous imbalanced datasets exist in modern machine learning dilemmas. Challenges of
generalization and fairness stem from the existence of underrepresented classes with …

Software defect prediction aims to automatically determine the most likely location of
defective program elements (ie, statement, method, class, module etc.). Previous studies for …

The purpose of this study is to experimentally design the drying, calcination, and sintering
processes of artificial lightweight aggregates through the orthogonal array, to expand the …

Improving software quality by predicting faults during the early stages of software
development is a primary goal of software fault prediction (SFP). Various machine learning …

Machine learning‐based software defect prediction (SDP) approaches have been
commonly proposed to help to deliver high‐quality software. Unfortunately, all the previous …

Success in software projects is now an important challenge. The main focus of the
engineering community is to predict software defects based on the history of classes and …

Successful software projects are now an important challenge, the main focus of the
engineering community being to predict software failures based on the history of buggy …