Two primary issues have emerged in the machine learning and data mining community: how
to deal with imbalanced data and how to choose appropriate features. These are of …

Software defect prediction is the process of locating defective modules in software. It
facilitates testing efficiency and consequently software quality. It enables a timely …

Two important problems which can affect the performance of classification models are high-
dimensionality (an overabundance of independent features in the dataset) and imbalanced …

In order to improve the effect of software defect prediction, many algorithms including feature
selection, have been proposed. Based on Wrapper and Filter hybrid framework, a feature …

Context Several issues hinder software defect data including redundancy, correlation,
feature irrelevance and missing samples. It is also hard to ensure balanced distribution …

Testing is considered as one of the expensive activities in software development process.
Fixing the defects during testing process can increase the cost as well as the completion …

The early prediction of defective modules in developing software can help the development
team to utilize the available resources efficiently to deliver high quality software product in …

An essential objective of software development is to locate and fix defects ahead of
schedule that could be expected under diverse circumstances. Many software development …

Software defect prediction models are used for predicting high risk software components.
Feature selection has significant impact on the prediction performance of the software defect …

Software defect prediction models that use software metrics such as code-level
measurements and defect data to build classification models are useful tools for identifying …