Improving Software Defect Prediction in Noisy Imbalanced Datasets

Improving Software Defect Prediction in Noisy Imbalanced Datasets

Software defect prediction is a popular method for optimizing software testing and improving software quality and reliability. However, software defect datasets usually have quality problems, such as class imbalance and data noise. Oversampling by generating the minority class samples is one of the...

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Bibliographic Details
Main Authors: Haoxiang Shi, Jun Ai, Jingyu Liu, Jiaxi Xu
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Applied Sciences
Subjects:
software defect prediction
class imbalance
undersampling
propensity score matching
oversampling
noise reduction
Online Access:https://www.mdpi.com/2076-3417/13/18/10466

Internet

https://www.mdpi.com/2076-3417/13/18/10466

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