Imbalanced software fault datasets, having fewer faulty modules than the nonfaulty modules,
make accurate fault prediction difficult. It is challenging for software practitioners to handle …

The Software fault prediction (SFP) target is to distinguish between faulty and non-faulty
modules. The prediction model's performance is vulnerable to the class imbalance issue in …

Software defect prediction is important to identify defects in the early phases of software
development life cycle. This early identification and thereby removal of software defects is …

Context: Software defect prediction (SDP) is an important challenge in the field of software
engineering, hence much research work has been conducted, most notably through the use …

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 …

Software systems are now ubiquitous and are used every day for automation purposes in
personal and enterprise applications; they are also essential to many safety-critical and …

Software defect prediction is a popular method for optimizing software testing and improving
software quality and reliability. However, software defect datasets usually have quality …

With the availability of high-speed Internet and the advent of Internet of Things devices,
modern software systems are growing in both size and complexity. Software defect …

In practice, Software Defect Prediction (SDP) models often suffer from highly imbalanced
data, which makes classifiers difficult to identify defective instances. Recently, many …

The software testing phase requires considerable time, effort, and cost, particularly when
there are many faults. Thus, developers focus on the evolution of Software Fault Prediction …