Cross-version defect prediction: use historical data, cross-project data, or both?
Author:
Funder
Japan Society for the Promotion of Science
Publisher
Springer Science and Business Media LLC
Subject
Software
Link
http://link.springer.com/content/pdf/10.1007/s10664-019-09777-8.pdf
Reference77 articles.
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3. Arisholm E, Briand LC (2006) Predicting fault-prone components in a java legacy system. In: Proc. of ISESE ’06. ACM, pp 1–10
4. Bennin KE, Toda K, Kamei Y, Keung J, Monden A, Ubayashi N (2016) Empirical evaluation of cross-release effort-aware defect prediction models. In: Proc. of QRS ’16. IEEE, pp 214–221
5. Bin Y, Zhou K, Lu H, Zhou Y, Xu B (2017) Training data selection for cross-project defection prediction: which approach is better? In: Proc. of ESEM ’17. IEEE, pp 354–363
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