PatchScope: LLM-Enhanced Fine-Grained Stable Patch Classification for Linux Kernel
Stable patch classification plays a crucial role in vulnerability management for the Linux kernel, significantly contributing to the stability and security of Long-term support~(LTS) versions. Although existing tools have effectively assisted in assessing whether patches should be merged into stable versions, they cannot determine which stable patches should be merged into which LTS versions. This process still requires the maintainers of the distribution community to manually screen based on the requirements of their respective versions. To address this issue, we propose PatchScope, which is designed to predict the specific merge status of patches. Patchscope consists of two components: patch analysis and patch classification. Patch analysis leverages Large Language Models~(LLMs) to generate detailed patch descriptions from the commit message and code changes, thereby deepening the model’s semantic understanding of patches. Patch classification utilizes a pre-trained language model to extract semantic features of the patches and employs a two-stage classifier to predict the merge status of the patches. The model is optimized using the dynamic weighted loss function to handle data imbalance and improve overall performance. Given that the primary focus is maintaining Linux kernel versions 5.10 and 6.6, we have conducted comparative experiments based on these two versions. Experimental results demonstrate that Patchscope can effectively predict the merge status of patches.
Wed 25 JunDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
11:00 - 12:30 | Program RepairTool Demonstrations / Research Papers at Aurora A Chair(s): Yannic Noller Ruhr University Bochum | ||
11:00 25mTalk | LLM Hallucinations in Practical Code Generation: Phenomena, Mechanism, and Mitigation Research Papers Ziyao Zhang Sun Yat-sen University, Chong Wang Nanyang Technological University, Yanlin Wang Sun Yat-sen University, Ensheng Shi Xi’an Jiaotong University, Yuchi Ma Huawei Cloud Computing Technologies, Wanjun Zhong Sun Yat-sen University, Jiachi Chen Sun Yat-sen University, Mingzhi Mao Sun Yat-sen University, Zibin Zheng Sun Yat-sen University DOI | ||
11:25 25mTalk | AdverIntent-Agent: Adversarial Reasoning for Repair Based on Inferred Program Intent Research Papers He Ye University College London (UCL), Aidan Z.H. Yang Carnegie Mellon University, Chang Hu Macau University of Science and Technology, Yanlin Wang Sun Yat-sen University, Tao Zhang Macau University of Science and Technology, Claire Le Goues Carnegie Mellon University DOI | ||
11:50 25mTalk | PatchScope: LLM-Enhanced Fine-Grained Stable Patch Classification for Linux Kernel Research Papers Rongkai Liu Central South University, Heyuan Shi Central South University, Shuning Liu Central South University, China, Chao Hu Central South University, Sisheng Li Central South University, China, Yuheng Shen Tsinghua University, Runzhe Wang Alibaba Group, Xiaohai Shi Alibaba Group, Yu Jiang Tsinghua University DOI | ||
12:15 15mDemonstration | InfraFix: Technology-Agnostic Repair of Infrastructure as Code Tool Demonstrations Nuno Saavedra INESC-ID and IST, University of Lisbon, João F. Ferreira INESC-ID and IST, University of Lisbon, Alexandra Mendes Faculty of Engineering, University of Porto & INESC TEC |
Aurora A is the first room in the Aurora wing.
When facing the main Cosmos Hall, access to the Aurora wing is on the right, close to the side entrance of the hotel.