DiverseVul: A New Vulnerable Source Code Dataset for Deep Learning Based Vulnerability Detection-Reference-Cited by-同舟云学术

DiverseVul: A New Vulnerable Source Code Dataset for Deep Learning Based Vulnerability Detection

Published:2023-10-16 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses
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Author:

Chen Yizheng¹^ORCID,Ding Zhoujie²^ORCID,Alowain Lamya³^ORCID,Chen Xinyun⁴^ORCID,Wagner David²^ORCID

Affiliation:

1. University of Maryland, United States of America

2. University of California, Berkeley, USA

3. King Abdulaziz City for Science and Technology, Saudi Arabia

4. Google Deepmind, United States of America

Funder

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3607199.3607242

Reference33 articles.

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3. NatGen: generative pre-training by “naturalizing” source code

4. Saikat Chakraborty , Rahul Krishna , Yangruibo Ding , and Baishakhi Ray . 2021. Deep learning based vulnerability detection: Are we there yet . IEEE Transactions on Software Engineering ( 2021 ). Saikat Chakraborty, Rahul Krishna, Yangruibo Ding, and Baishakhi Ray. 2021. Deep learning based vulnerability detection: Are we there yet. IEEE Transactions on Software Engineering (2021).

5. Building a Commit-level Dataset of Real-world Vulnerabilities

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