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 …

One of the most well-known study areas in computer science is software defect prediction. It
aims to find defects occurring from the method level code, so it can be used to better …

Imbalanced data is a common problem in data mining when dealing with classification
problems, where samples of a class vastly outnumber other classes. In this situation, many …

Software defect prediction is a highly studied domain in Software Engineering research due
to its importance in software development. In literature, various classification methods with …

Experimental studies confirmed that only a small portion of software modules cause faults in
software systems. Therefore, the majority of software modules are represented with non …

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 …

Class imbalance has drawn much attention of researchers in software defect prediction. In
practice, the performance of defect prediction models may be affected by the class …

The performance of prediction models in software defect prediction depends on the quality
of datasets used for training such models. Class imbalance is one of data quality problems …

Software defect prediction performance varies over a large range. Menzies suggested there
is a ceiling effect of 80% Recall [8]. Most of the data sets used are highly imbalanced. This …

Fault prediction problem has a crucial role in the software development process because it
contributes to reducing defects and assisting the testing process towards fault-free software …