Building an ensemble for software defect prediction based on diversity selection
Background: Ensemble techniques have gained attention in various scientific fields. Defect
prediction researchers have investigated many state-of-the-art ensemble models and …
prediction researchers have investigated many state-of-the-art ensemble models and …
[PDF][PDF] Combining particle swarm optimization based feature selection and bagging technique for software defect prediction
The costs of finding and correcting software defects have been the most expensive activity in
software development. The accurate prediction of defect‐prone software modules can help …
software development. The accurate prediction of defect‐prone software modules can help …
[HTML][HTML] Software Defect Prediction Analysis Using Machine Learning Techniques
There is always a desire for defect-free software in order to maintain software quality for
customer satisfaction and to save testing expenses. As a result, we examined various known …
customer satisfaction and to save testing expenses. As a result, we examined various known …
[HTML][HTML] A comparison of semi-supervised classification approaches for software defect prediction
C Catal - Journal of Intelligent Systems, 2014 - degruyter.com
Predicting the defect-prone modules when the previous defect labels of modules are limited
is a challenging problem encountered in the software industry. Supervised classification …
is a challenging problem encountered in the software industry. Supervised classification …
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 …
ELM and KELM based software defect prediction using feature selection techniques
I Arora, A Saha - Journal of Information and Optimization Sciences, 2019 - Taylor & Francis
Context: Software defect prediction (SDP) models help in delivering a dependable and a
genuine product to the clients. However, the performance of these models is affected by the …
genuine product to the clients. However, the performance of these models is affected by the …
Revisiting the class imbalance issue in software defect prediction
Software defect prediction is related to the testing area of software industry. Several methods
have been developed for the prediction of bugs in software source codes. The objective of …
have been developed for the prediction of bugs in software source codes. The objective of …
Data sampling-based feature selection framework for software defect prediction
AO Balogun, FB Lafenwa-Balogun, HA Mojeed… - … and Technologies for …, 2021 - Springer
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 …
negative effect on the predictive capabilities of prediction models in software defect …
Software fault proneness prediction: A comparative study between bagging, boosting, and stacking ensemble and base learner methods
Modules with defects might be the prime reason for decreasing the software quality and
increasing the cost of maintenance. Therefore, the prediction of faulty modules of systems …
increasing the cost of maintenance. Therefore, the prediction of faulty modules of systems …
Software defect prediction based on kernel PCA and weighted extreme learning machine
Context Software defect prediction strives to detect defect-prone software modules by mining
the historical data. Effective prediction enables reasonable testing resource allocation …
the historical data. Effective prediction enables reasonable testing resource allocation …