Deployment of a change‐level software defect prediction solution into an industrial setting
Author:
Affiliation:
1. Faculty of Computer and Informatics Engineering Istanbul Technical University Istanbul Turkey
2. Ericsson Istanbul Turkey
Publisher
Wiley
Subject
Software
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/smr.2381
Reference70 articles.
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3. YangY ZhouY LiuJ et al.Effort‐aware just‐in‐time defect prediction: simple unsupervised models could be better than supervised models. In: Proceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering.2016:157–168.
4. Effort-aware and just-in-time defect prediction with neural network
5. YuX BenninKE LiuJ KeungJW YinX XuZ.An Empirical Study of Learning to Rank Techniques for Effort‐Aware Defect Prediction. In: 2019 IEEE 26th International Conference on Software Analysis Evolution and Reengineering (SANER);2019:298–309.
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