An empirical study of data sampling techniques for just-in-time software defect prediction
Author:
Funder
National Natural Science Foundation of China
Natural Science Basic Research Program of Shaanxi Province
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10515-024-00455-8.pdf
Reference60 articles.
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3. Bennin, K.E., Tahir, A., MacDonell, S.G., et al.: An empirical study on the effectiveness of data resampling approaches for cross-project software defect prediction. IET Softw. 16, 185–199 (2022)
4. Cabral, G.G., Minku, L.L.: Towards reliable online just-in-time software defect prediction. IEEE Trans. Softw. Eng. 49(3), 1342–1358 (2023)
5. Cabral, G.G., Minku, L.L., Shihab, E., et al.: Class imbalance evolution and verification latency in just-in-time software defect prediction. In: 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE), pp. 666–676 (2019)
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