Vulnerability Detection with Representation Learning
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-0272-9_8
Reference28 articles.
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2. Hazimeh, A., Herrera, A., Payer, M.: Magma: a ground-truth fuzzing benchmark. Proc. ACM Meas. Anal. Comput. Syst. 4(3), 1–29 (2020)
3. Ferrara, P., Mandal, A.K., Cortesi, A., et al.: Static analysis for discovering IoT vulnerabilities. Int. J. Softw. Tools Technol. Trans. 23(1), 71–88 (2021)
4. Pecorelli, F., Lujan, S., Lenarduzzi, V., et al.: On the adequacy of static analysis warnings with respect to code smell prediction. Empir. Softw. Eng. 27(3), 1–44 (2022)
5. Palit, T., Moon, J.F., Monrose, F., et al.: Dynpta: combining static and dynamic analysis for practical selective data protection. In: 2021 IEEE Symposium on Security and Privacy (SP). IEEE, pp. 1919–1937 (2021)
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