Sep 2026· International Conference on Automated Software Engineering· Vol 33· 0 citations· 36 references
TL;DR
HSF-Vul is proposed, a novel approach for software vulnerability detection and localization based on hierarchical semantic fusion that frame vulnerability detection as a binary classification task and extend it to line-level localization by analyzing the contribution of individual code lines.
Detecting vulnerabilities in software development is crucial yet challenging. Deep learning-based approaches have shown promise in automatically learning features for vulnerable function detection. In practice, human analysts need to correlate the behavioral logic of multiple functions to confirm the occurrence of vuln...
Hong-Jun Huang, Fu-Tai Zou, Jia-Ping Gui et al.· ACM Transactions on Software...· 0 citations
Experimental results show that AST-based structural features substantially improve recall compared with the TF-IDF baseline, while the combined TF-IDF and AST representation maintains this improved performance.
Vani Pasupula, M. N. V. Manikanth, Nagaraju Vassey· International Journal of Cre...· 0 citations
Software vulnerabilities represent an enduring threat to modern cyberspace. Effective vulnerability detection increasingly relies on reasoning about complex program semantics, structural dependencies, and execution behaviors. Consequently, extracting vulnerability-relevant features from code efficiently has become a pr...
Jun-Jie Wang, Tong Yu, Ming Li et al.· Transactions on Graph Intell...· 0 citations
Smart contracts facilitate and enforce agreements between untrusted parties without trusted intermediaries, but vulnerabilities within contracts can cause severe damage once exploited. Various analysis techniques have been proposed for vulnerability detection, but they are typically limited to specific vulnerability ty...
Jun-Xiang Wang, Fu Song, Miao-Miao Zhang et al.· 0 citations
A unified framework combining a novel Hierarchical Cross-Attention Subgraph Neural Network for detection with Large Language Models for explanation form a comprehensive framework that significantly enhances both the technical accuracy and operational usability of smart contract analysis.
Smart contracts operate in decentralized environments where deployed code cannot be easily modified, making security vulnerabilities particularly critical. Even minor logical flaws may lead to severe financial and operational consequences. Although traditional static analysis and symbolic execution techniques have been...
R. S, Mahantesh Mathapati· Journal of Artificial Intell...· 0 citations
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