Cross-Project Software Defect Prediction Based on Feature Selection and Knowledge Distillation
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-5594-3_12
Reference23 articles.
1. Li, Z., Zhang, H., Jing, X.Y., et al.: DSSDPP: data selection and sampling based domain programming predictor for cross-project defect prediction. IEEE Trans. Softw. Eng. (2022)
2. Sun, Z., Li, J., Sun, H., et al.: CFPS: collaborative filtering based source projects selection for cross-project defect prediction. Appl. Soft Comput. 99, 106940 (2021)
3. Arar, Ö.F., Ayan, K.: A feature dependent Naive Bayes approach and its application to the software defect prediction problem. Appl. Soft Comput. 59, 197–209 (2017)
4. Jin, C.: Cross-project software defect prediction based on domain adaptation learning and optimization. Expert Syst. Appl. 171, 114637 (2021)
5. Zhuang, F., Qi, Z., Duan, K., et al.: A comprehensive survey on transfer learning. Proc. IEEE 109(1), 43–76 (2020)
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