Software defect prediction using ensemble learning: A systematic literature review
Recent advances in the domain of software defect prediction (SDP) include the integration of
multiple classification techniques to create an ensemble or hybrid approach. This technique …
multiple classification techniques to create an ensemble or hybrid approach. This technique …
Software fault prediction using data mining, machine learning and deep learning techniques: A systematic literature review
Software fault/defect prediction assists software developers to identify faulty constructs, such
as modules or classes, early in the software development life cycle. There are data mining …
as modules or classes, early in the software development life cycle. There are data mining …
Software defect prediction using tree-based ensembles
H Aljamaan, A Alazba - Proceedings of the 16th ACM international …, 2020 - dl.acm.org
Software defect prediction is an active research area in software engineering. Accurate
prediction of software defects assists software engineers in guiding software quality …
prediction of software defects assists software engineers in guiding software quality …
An empirical study of ensemble techniques for software fault prediction
SS Rathore, S Kumar - Applied Intelligence, 2021 - Springer
Previously, many researchers have performed analysis of various techniques for the
software fault prediction (SFP). Oddly, the majority of such studies have shown the limited …
software fault prediction (SFP). Oddly, the majority of such studies have shown the limited …
Software defect prediction using stacking generalization of optimized tree-based ensembles
A Alazba, H Aljamaan - Applied Sciences, 2022 - mdpi.com
Software defect prediction refers to the automatic identification of defective parts of software
through machine learning techniques. Ensemble learning has exhibited excellent prediction …
through machine learning techniques. Ensemble learning has exhibited excellent prediction …
Software fault prediction based on the dynamic selection of learning technique: findings from the eclipse project study
SS Rathore, S Kumar - Applied Intelligence, 2021 - Springer
An effective software fault prediction (SFP) model could help developers in the quick and
prompt detection of faults and thus help enhance the overall reliability and quality of the …
prompt detection of faults and thus help enhance the overall reliability and quality of the …
Comparative analysis of software fault prediction using various categories of classifiers
The quality of the software being developed varies with the size and complexity of the
software. It is a matter of concern in software development as it impairs the faith of customers …
software. It is a matter of concern in software development as it impairs the faith of customers …
Predicting software maintainability in object-oriented systems using ensemble techniques
Prediction of the maintainability of classes in object-oriented systems is a significant factor
for software success, however it is a challenging task to achieve. To date, several machine …
for software success, however it is a challenging task to achieve. To date, several machine …
SMOTEFRIS-INFFC: Handling the challenge of borderline and noisy examples in imbalanced learning for software defect prediction
Abstract The object of Software Defect Prediction (SDP) is to identify modules that are prone
to defect. This is achieved by training prediction models with datasets obtained by mining …
to defect. This is achieved by training prediction models with datasets obtained by mining …
A three-stage based ensemble learning for improved software fault prediction: an empirical comparative study
Abstract Software Fault Prediction (SFP) research has made enormous endeavor to
accurately predict fault proneness of software modules, thus maximize precious software test …
accurately predict fault proneness of software modules, thus maximize precious software test …