An Interpretable Vulnerability Detection Framework Based on Multi-task Learning
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-8178-6_18
Reference32 articles.
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3. Hin, D., Kan, A., Chen, H., Babar, M.A.: LineVD: statement-level vulnerability detection using graph neural networks. In: Proceedings of the 19th International Conference on Mining Software Repositories, pp. 596–607 (2022)
4. Napier, K., Bhowmik, T., Wang, S.: An empirical study of text-based machine learning models for vulnerability detection. Empir. Softw. Eng. 28(2), 38 (2023)
5. Sun, H., et al.: VDSimilar: vulnerability detection based on code similarity of vulnerabilities and patches. Comput. Secur. 110, 102417 (2021)
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