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An empirical study on the effectiveness of data resampling approaches for cross-project software defect prediction.

, , , and . IET Softw., 16 (2): 185-199 (2022)

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Cross-Project Defect Prediction Using a Credibility Theory Based Naive Bayes Classifier., , , , and . QRS, page 434-441. IEEE, (2017)MAHAKIL: diversity based oversampling approach to alleviate the class imbalance issue in software defect prediction., , , , and . ICSE, page 699. ACM, (2018)A Stratification and Sampling Model for Bellwether Moving Window., , , , and . SEKE, page 481-486. KSI Research Inc. and Knowledge Systems Institute Graduate School, (2017)Towards Requirements Engineering Activities for Machine Learning-Enabled FinTech Applications., , , , , and . APSEC, page 121-130. IEEE, (2023)Building Defect Prediction Models by Online Learning Considering Defect Overlooking., , , , , , , and . CoRR, (2024)Revisiting the Impact of Concept Drift on Just-in-Time Quality Assurance., , , and . QRS, page 53-59. IEEE, (2020)Agile Requirements Engineering in a Distributed Environment: Experiences from the Software Industry During Unprecedented Global Challenges., , , , , and . COMPSAC, page 682-691. IEEE, (2024)Using Bandit Algorithms for Selecting Feature Reduction Techniques in Software Defect Prediction., , , , , , , and . MSR, page 670-681. ACM, (2022)Investigating the Significance of the Bellwether Effect to Improve Software Effort Prediction: Further Empirical Study., , , , and . IEEE Trans. Reliability, 67 (3): 1176-1198 (2018)Rework Effort Estimation of Self-admitted Technical Debt., , , and . QuASoQ/TDA@APSEC, volume 1771 of CEUR Workshop Proceedings, page 72-75. CEUR-WS.org, (2016)