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To tackle this challenge, we propose CoLeFunDa: a framework consisting of a Contrastive Learner and FunDa, which is a novel approach for Function change Data ...
In this work, we propose a framework, CoLeFunDa, for explainable vulnerability silent fix identification. CoLeFunDa leverages a novel function change ...
Jul 26, 2023 · To tackle this challenge, we propose CoLeFunDa: a framework consisting of a Contrastive Learner and FunDa, which is a novel approach for ...
However, it is challenging to identify silent fixes and provide explanations due to the limited and diverse data. To tackle this challenge, we propose CoLeFunDa ...
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In this work, we propose a framework, CoLeFunDa, for explainable vulnerability silent fix identification. CoLeFunDa leverages a novel function change ...
The paper compares the efficiency of single and double attack against a system consisting of identical parallel elements. An attacker maximizes the system ...
CoLeFunDa: Explainable Silent Vulnerability Fix Identification (2023); Fine-grained Commit-level Vulnerability Type Prediction by CWE Tree Structure (2023) ...
Sep 15, 2023 · “Colefunda: Explainable silent vulnerability fix identification,” 2023. [8] Z. Feng, D. Guo, D. Tang, N. Duan, X. Feng, M. Gong, L. Shou, B ...
2022. Colefunda: Explainable silent vulnerability fix identification. J Zhou, M Pacheco, J Chen, X Hu, X Xia, D Lo, AE Hassan. 2023 IEEE/ACM 45th International ...
Chronos: Time-Aware Zero-Shot Identification of Libraries from Vulnerability Reports; CoLeFunDa: Explainable Silent Vulnerability Fix Identification ...