Software Defect Prediction Method Based on Cost-Sensitive Random Forest

Author:

Zhao Wei-Dong,Zhang Sheng-Dong,Wang Ming

Publisher

Springer International Publishing

Reference21 articles.

1. Cai, L., Fan, Y., Yan, M., Xia, X.: Research progress in real-time software defect prediction. J. Softw. 30(5), 1288–1307 (2019)

2. Nagappan, N., Ball, T.: Use of relative code churn measures to predict system defect density. In: Proceedings of the 27th International Conference on Software Engineering (ICSE 2005), pp. 284–292 (2005)

3. Compton, B.T., Withrow, C.: Prediction and control of ADA software defects. J. Syst. Softw. 12, 199–207 (1990)

4. Menzies, T., DiStefano, J.S., Orrego, A.S.: Assessing Predictors of Software Defects (2004)

5. Xing, F., Guo, P., Lyu, M.R.: A novel method for early software quality prediction based on support vector machine. In: 16th IEEE International Symposium on Software Reliability Engineering (ISSRE 2005), vol. 10, p. 222 (2005)

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