An empirical study on pareto based multi-objective feature selection for software defect prediction
The performance of software defect prediction (SDP) models depend on the quality of
considered software features. Redundant features and irrelevant features may reduce the …
considered software features. Redundant features and irrelevant features may reduce the …
An empirical study on the effectiveness of feature selection for cross-project defect prediction
Software defect prediction has attracted much attention of researchers in software
engineering. At present, feature selection approaches have been introduced into software …
engineering. At present, feature selection approaches have been introduced into software …
A framework for software defect prediction and metric selection
Automated software defect prediction is an important and fundamental activity in the domain
of software development. However, modern software systems are inherently large and …
of software development. However, modern software systems are inherently large and …
Software defect prediction based on enhanced metaheuristic feature selection optimization and a hybrid deep neural network
K Zhu, S Ying, N Zhang, D Zhu - Journal of Systems and Software, 2021 - Elsevier
Software defect prediction aims to identify the potential defects of new software modules in
advance by constructing an effective prediction model. However, the model performance is …
advance by constructing an effective prediction model. However, the model performance is …
A feature selection model for software defect prediction using binary Rao optimization algorithm
K Thirumoorthy - Applied Soft Computing, 2022 - Elsevier
In this digital world, using software has become an important part of daily life and business.
The software must be rigorously tested in order to avert a financial crisis. The defect-free …
The software must be rigorously tested in order to avert a financial crisis. The defect-free …
Impact of feature selection methods on the predictive performance of software defect prediction models: an extensive empirical study
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) …
many FS methods have been proposed in the context of software defect prediction (SDP) …
Performance analysis of feature selection methods in software defect prediction: a search method approach
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 systems. The quality of SDP models depends largely on the quality of software …
A cluster based feature selection method for cross-project software defect prediction
Cross-project defect prediction (CPDP) uses the labeled data from external source software
projects to compensate the shortage of useful data in the target project, in order to build a …
projects to compensate the shortage of useful data in the target project, in order to build a …
Search-based wrapper feature selection methods in software defect prediction: an empirical analysis
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 …
capabilities of prediction models in software defect prediction (SDP). As a viable solution …
A comparative study of iterative and non-iterative feature selection techniques for software defect prediction
TM Khoshgoftaar, K Gao, A Napolitano… - Information Systems …, 2014 - Springer
Two important problems which can affect the performance of classification models are high-
dimensionality (an overabundance of independent features in the dataset) and imbalanced …
dimensionality (an overabundance of independent features in the dataset) and imbalanced …