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.
FiCoVuL is presented, a framework for analyzing interconnected functions and providing fine-grained guidance for vulnerability fixing that significantly outperforms other methods in both vulnerability detection and localization.
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
This work proposes a novel neuro-symbolic approach to static analysis, named ELSA, which comprises two key modules, namely, LLM-assisted static analysis and analyzer ensemble (the ensemble of multiple LLM-assisted static analyzers), each incorporating two distinct strategies.
Jun-Xiang Wang, Fu Song, Miao-Miao Zhang et al.· Proceedings of the ACM on So...· 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.
Results indicate that integrating semantic richness and structural awareness within a Contextual Encoding Network architecture enhances both detection reliability and generalization capability, making the framework suitable for practical smart contract security analysis.
R. S, Mahantesh Mathapati· Journal of Artificial Intell...· 0 citations
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