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Finding the best learning to rank algorithms for effort-aware defect prediction.

, , , , , , , и . Inf. Softw. Technol., (мая 2023)

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Jacky Estublier

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Cross-Project Defect Prediction Using a Credibility Theory Based Naive Bayes Classifier., , , , и . QRS, стр. 434-441. IEEE, (2017)Improving effort-aware defect prediction by directly learning to rank software modules., , , , , , , и . Inf. Softw. Technol., (января 2024)Improving domain-specific neural code generation with few-shot meta-learning., , , , , , , и . Inf. Softw. Technol., (февраля 2024)On the relative value of imbalanced learning for code smell detection., , , , , и . Softw. Pract. Exp., 53 (10): 1902-1927 (октября 2023)Where Are Large Language Models for Code Generation on GitHub?, , , , , и . CoRR, (2024)The Impact of the bug number on Effort-Aware Defect Prediction: An Empirical Study., , , , , и . Internetware, стр. 67-78. ACM, (2023)Revisiting 'revisiting supervised methods for effort-aware cross-project defect prediction'., , , , , и . IET Softw., 17 (4): 472-495 (августа 2023)A Heuristic Rule Reduction Approach to Software Fault-proneness Prediction., , , , и . APSEC, стр. 838-847. IEEE, (2012)New Technique for Stock Trend Analysis - Volume-weighted Squared Moving Average Convergence & Divergence., и . COMPSAC, стр. 987-988. IEEE, (2023)Fight Fire with Fire: How Much Can We Trust ChatGPT on Source Code-Related Tasks?, , , , , и . CoRR, (2024)