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Recent advancements in large language models (LLMs) have highlighted the potential for vulnerability detection, a crucial component of software quality assurance.
Z. Li et al. , “Sysevr: A framework for using deep learning to detect software vulnerabilities,” IEEE Trans. on Dependable and Secure Computing , 2022
2022
Earlier work this paper cites.
Z. Li et al. , “On the effectiveness of function-level vulnerability detectors for inter-procedural vulnerabilities,” ICSE , 2024
2024
Earlier work this paper cites.
B. Steenhoek et al. , “Dataflow analysis-inspired deep learning for efficient vulnerability detection,” ICSE , 2024
2024
Cited alongside, same era.
C. Zhang et al. , “Prompt-enhanced software vulnerability detection using chatgpt,” ICSE , 2024
2024
Cited alongside, same era.
Y. Nong et al. , “Chain-of-thought prompting of large language models for discovering and fixing software vulnerabilities,” 2024
2024
Closest in time.
X. Zhou et al. , “Large language model for vulnerability detection: Emerging results and future directions,” ICSE , 2024
2024
Closest in time.
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