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Detection of defect-prone software modules is an important topic in software quality research, and widely studied under enough defect data circumstance. An improved semi-supervised learning approach for defect detection involving class imbalanced and limited labeled data problem has been proposed. This approach employs random under-sampling technique to resample the original training set and updating...
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