Software fault/defect prediction assists software developers to identify faulty constructs, such
as modules or classes, early in the software development life cycle. There are data mining …

In recent years, most researchers focused on the classification problems of imbalanced data
sets, and these problems are widely distributed in industrial production and medical …

The method of recognizing faults in a software system is acknowledged as software fault
prediction. Software faults predicted in prior stages help in the management of resources …

Abstract Unsupervised Effort-Aware Defect Prediction (EADP) uses unlabeled data to
construct a model and ranks software modules according to the software feature values. Xu …

Recently, the high usage of online learning platforms by schools and universities has been
correlated with an increasing incompletion rate of online courses. Predicting students' …

Nowadays, many classification algorithms have been applied to various industries to help
them work out their problems met in real-life scenarios. However, in many binary …

Software defect detection (SDD) is crucial to ensure the reliability of software systems and
identify defects in classification. One of the key challenges in defect detection is to select …

Predicting software faults at the primary stage is a challenging role for software engineers
and tech industries. During the development of software projects, it is necessary to predict …

The imbalanced nature of the software datasets leads to the biased learning of prediction
model toward the observations of the majority class (non-defective class). The prediction …

The process of accurately predicting software defects is highly crucial during the early period
of software development before testing activities begin. A variety of computational methods …