Feature selection is known to be an applicable solution to address the problem of high
dimensionality in software defect prediction (SDP). However, choosing an appropriate filter …

Selecting the most suitable filter method that will produce a subset of features with the best
performance remains an open problem that is known as filter rank selection problem. A …

The high dimensionality of software metric features has long been noted as a data quality
problem that affects the performance of software defect prediction (SDP) models. This …

With the variety of different filter methods, selecting the most appropriate filter method which
gives the best performance is a difficult task. Filter rank selection and stability problems …

Feature selection (FS) is a feasible solution for mitigating high dimensionality problem, and
many FS methods have been proposed in the context of software defect prediction (SDP) …

High dimensionality is a data quality problem that negatively influences the predictive
capabilities of prediction models in software defect prediction (SDP). As a viable solution …

Software Defect Prediction (SDP) models are built using software metrics derived from
software systems. The quality of SDP models depends largely on the quality of software …

Software defect prediction (SDP) is a hot topic in the modern software engineering research
community. It has been used for evaluating software quality and reliability and allocating …

The performance of software defect prediction (SDP) models depend on the quality of
considered software features. Redundant features and irrelevant features may reduce the …

High dimensionality and class imbalance are latent data quality problems that have a
negative effect on the predictive capabilities of prediction models in software defect …