Siyuan Li, Jiayi Zhou, Zhiyuan Xia, Weijie Wang, Yaowen Zheng, Weiran Tang, Hong Li, Hongsong Zhu · 2026 · arXiv
DOI: 10.48550/arXiv.2610.27871 · open-access PDF
Mengidentifikasi apakah patch hadir sangat penting, tetapi metode tradisional menderita penggunaan dan akurasi yang terbatas, sering tergantung pada proses kompilasi yang rapuh. Dalam pekerjaan kami sebelumnya, kami memperkenalkan Lares, kerangka kerja bebas kompilasi pertama untuk pengujian kehadiran patch yang menggabungkan model bahasa besar (LLM) dengan pemecah SMT. Namun, Lares memperlakukan LLM dan pemecah SMT sebagai dua saluran keputusan yang terpisah dan paralel: saluran simbolik (Z3) berhasil dalam hanya 20% dari
Machine translation (Meta M2M100); the English original follows.
Code reuse in modern software ecosystems facilitates the spread of 1-day vulnerabilities, posing significant security risks. Determining if patches are present is crucial, but traditional methods suffer from limited usability and accuracy, often depending on a fragile compilation process. In our prior work, we introduced Lares, the first compilation-free framework for patch presence testing that combines large language models (LLMs) with SMT solvers. However, Lares treats the LLM and the SMT solver as two separate, parallel decision channels: the symbolic channel (Z3) succeeded in only 20% of
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