Cross‐version defect prediction using threshold‐based active learning
Published in Journal of Software Evolution and Process • Apr 2, 2023
NobleIDNI2P38W72R20S33
Authors:,,
Yuanqing Mei
Xutong Liu
Zeyu Lu
Abstract
Abstract Because defects in software modules (e.g., classes) might lead to product failure and financial loss, software defect prediction enables us to better understand and control software quality. Software development is a dynamic evolutionary process that may result in data distributions (e.g., ...
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