Improving the Quality of Software Vulnerability Patch Datasets Using Uncertainty Quantification

This research proposes a novel approach to curate software vulnerability patch datasets by leveraging uncertainty quantification (UQ) techniques in machine learning, leading to improved accuracy and efficiency in downstream applications like vulnerability prediction.