Understanding and Tackling Label Errors in Deep Learning-Based Vulnerability Detection (Experience Paper)-Reference-Cited by-同舟云学术

Understanding and Tackling Label Errors in Deep Learning-Based Vulnerability Detection (Experience Paper)

Published:2023-07-12 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis
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Author:

Nie Xu¹,Li Ningke²,Wang Kailong²,Wang Shangguang³,Luo Xiapu⁴,Wang Haoyu²

Affiliation:

1. Huazhong University of Science and Technology, China / Beijing University of Posts and Telecommunications, China

2. Huazhong University of Science and Technology, China

3. Beijing University of Posts and Telecommunications, China

4. Hong Kong Polytechnic University, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3597926.3598037

Reference42 articles.

1. American Information Technology Laboratory. 2017. Software Assurance Reference Dataset. https://samate.nist.gov/SARD/index.php American Information Technology Laboratory. 2017. Software Assurance Reference Dataset. https://samate.nist.gov/SARD/index.php

2. American Information Technology Laboratory. 2021. National Vulnerability Database. https://nvd.nist.gov/ American Information Technology Laboratory. 2021. National Vulnerability Database. https://nvd.nist.gov/

3. Apple Inc. 2021. Clang static analyzer. https://clang-analyzer.llvm.org Apple Inc. 2021. Clang static analyzer. https://clang-analyzer.llvm.org

4. MVD

5. Deep Learning based Vulnerability Detection: Are We There Yet

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