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Code Churn: A Neglected Metric in Effort-Aware Just-in-Time Defect Prediction.

, , , , and . ESEM, page 11-19. IEEE Computer Society, (2017)

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The Influence of Developer Quality on Software Fault-Proneness Prediction., , , , , and . SERE, page 11-19. IEEE, (2014)An improved accuracy measure for rough sets., , and . J. Comput. Syst. Sci., 71 (2): 163-173 (2005)An AST-Based Approach to Classifying Defects., , , , , and . QRS Companion, page 14-21. IEEE, (2015)Are Slice-Based Cohesion Metrics Actually Useful in Effort-Aware Post-Release Fault-Proneness Prediction? An Empirical Study., , , , , , , and . IEEE Trans. Software Eng., 41 (4): 331-357 (2015)DMC: a more precise cohesion measure for classes., , , , , and . Information & Software Technology, 47 (3): 167-180 (2005)An empirical investigation into the effect of slice types on slice-based cohesion metrics., , , , , and . Information & Software Technology, (2016)A compile-time optimization framework for Ada rendezvous., , , and . SIGPLAN Notices, 39 (2): 18-25 (2004)Code Churn: A Neglected Metric in Effort-Aware Just-in-Time Defect Prediction., , , , and . ESEM, page 11-19. IEEE Computer Society, (2017)A Novel 4D Track-before-Detect Approach for Weak Targets Detection in Clutter Regions., , , , and . Remote. Sens., 13 (23): 4942 (2021)Content Analysis Based Medical Images Fusion with Fuzzy Inference., , and . FSKD (3), page 37-41. IEEE Computer Society, (2008)978-0-7695-3305-6.