Software defect prediction based on stacked sparse denoising autoencoders and enhanced extreme learning machine
Author:
Affiliation:
1. School of Computer Science Wuhan University Wuhan China
2. Artificial Intelligence Institute Shanghai Jiaotong University Shanghai China
Funder
National Natural Science Foundation of China
Publisher
Institution of Engineering and Technology (IET)
Subject
Computer Graphics and Computer-Aided Design
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1049/sfw2.12029
Reference62 articles.
1. Building Defect Prediction Models in Practice
2. Recalling the "imprecision" of cross-project defect prediction
3. A Study of Redundant Metrics in Defect Prediction Datasets
4. A comparative study of iterative and non-iterative feature selection techniques for software defect prediction
5. Deep Learning for Just-in-Time Defect Prediction
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