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Causally Remove Negative Confound Effects of Size Metric for Software Defect Prediction
2022
Applied Sciences
Software defect prediction technology can effectively detect potential defects in the software system. The most common method is to establish machine learning models based on software metrics for prediction. However, most of the prediction models are proposed without considering the confounding effects of size metric. The size metric has unexpected correlations with other software metrics and introduces biases into prediction results. Suitably removing these confounding effects to improve the
doi:10.3390/app12031387
fatcat:346574vlhvdnvhxydzm5ttqvqy