Software Defect Prediction Based on Deep Representation Learning of Source Code From Contextual Syntax and Semantic Graph
Author:
Affiliation:
1. School of Software, Northwestern Polytechnical University, Xi'an, China
2. Department of Computer Science, Hodeidah University, Al-Hudaydah, Yemen
3. Research Institute of Engineering and Technology, Hanyang University, Ansan, South Korea
Funder
Hanyang University, South Korea
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/24/10547161/10418777.pdf?arnumber=10418777
Reference48 articles.
1. Cross-Project and Within-Project Semisupervised Software Defect Prediction: A Unified Approach
2. Deep Semantic Feature Learning for Software Defect Prediction
3. A Novel Class-Imbalance Learning Approach for Both Within-Project and Cross-Project Defect Prediction
4. Deep Learning-Based Software Defect Prediction via Semantic Key Features of Source Code—Systematic Survey
5. SPE$^{2}$: Self-Paced Ensemble of Ensembles for Software Defect Prediction
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