Benchmarking Software Vulnerability Detection Techniques: A Survey
March 29, 2023 ยท The Cartographer ยท ๐ arXiv.org
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"Title-pattern auto-detect: Benchmarking Software Vulnerability Detection Techniques: A Survey"
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Authors
Yingzhou Bi, Jiangtao Huang, Penghui Liu, Lianmei Wang
arXiv ID
2303.16362
Category
cs.SE: Software Engineering
Citations
5
Venue
arXiv.org
Last Checked
3 days ago
Abstract
Software vulnerabilities can have serious consequences, which is why many techniques have been proposed to defend against them. Among these, vulnerability detection techniques are a major area of focus. However, there is a lack of a comprehensive approach for benchmarking these proposed techniques. In this paper, we present the first survey that comprehensively investigates and summarizes the current state of software vulnerability detection benchmarking. We review the current literature on benchmarking vulnerability detection, including benchmarking approaches in technique-proposing papers and empirical studies. We also separately discuss the benchmarking approaches for traditional and deep learning-based vulnerability detection techniques. Our survey analyzes the challenges of benchmarking software vulnerability detection techniques and the difficulties involved. We summarize the challenges of benchmarking software vulnerability detection techniques and describe possible solutions for addressing these challenges.
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