no code implementations • 4 Dec 2023 • Ashwin Kallingal Joshy, Mirza Sanjida Alam, Shaila Sharmin, Qi Li, Wei Le
We demonstrated that using our cleaned data, LineVul, a SOTA line-level vulnerability detection tool, detected 70 more vulnerable lines and 18 more vulnerable functions, and improved Top 10 accuracy from 66% to 73%.
no code implementations • 7 Nov 2023 • Benjamin Steenhoek, Md Mahbubur Rahman, Shaila Sharmin, Wei Le
Due to the different training objectives and the performance of the models, it is interesting to consider whether the models have learned the semantics of code relevant to vulnerability detection, namely bug semantics, and if so, how the alignment to bug semantics relates to model performance.