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检索条件"机构=Huawei Software Engineering Application Technology Lab"
126 条 记 录,以下是11-20 订阅
排序:
Code Change Intention, Development Artifact and History Vulnerability: Putting Them Together for Vulnerability Fix Detection by LLM
arXiv
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arXiv 2025年
作者: Yang, Xu Zhu, Wenhan Pacheco, Michael Zhou, Jiayuan Wang, Shaowei Hu, Xing Liu, Kui University of Manitoba WinnipegMB Canada Huawei Canada Canada Zhejiang University Hangzhou China Huawei Software Engineering Application Technology Lab Hangzhou China
Detecting vulnerability fix commits in open-source software is crucial for maintaining software security. To help OSS identify vulnerability fix commits, several automated approaches are developed. However, existing a... 详细信息
来源: 评论
A Survey on Modern Code Review: Progresses, Challenges and Opportunities
arXiv
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arXiv 2024年
作者: Yang, Zezhou Gao, Cuiyun Guo, Zhaoqiang Li, Zhenhao Liu, Kui Xia, Xin Zhou, Yuming Harbin Institute of Technology Shenzhen China Software Engineering Application Technology Lab Huawei Hangzhou China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China
Over the past decade, modern code review (MCR) has been deemed as a crucial practice of software quality assurance, which is applied to improve software quality and transfer development knowledge within a software tea... 详细信息
来源: 评论
Identify and Update Test Cases when Production Code Changes: A Transformer-Based Approach  23
Identify and Update Test Cases when Production Code Changes:...
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Proceedings of the 38th IEEE/ACM International Conference on Automated software engineering
作者: Xing Hu Zhuang Liu Xin Xia Zhongxin Liu Tongtong Xu Xiaohu Yang School of Software Technology Zhejiang University Ningbo China College of Computer Science and Technology Zhejiang University Hangzhou China Software Engineering Application Technology Lab Huawei Hangzhou China
software testing is one of the most essential parts of the software lifecycle and requires a substantial amount of time and effort. During the software evolution, test cases should coevolve with the production code. H... 详细信息
来源: 评论
Dual Prompt-Based Few-Shot Learning for Automated Vulnerability Patch Localization
Dual Prompt-Based Few-Shot Learning for Automated Vulnerabil...
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IEEE International Conference on software Analysis, Evolution and Reengineering (SANER)
作者: Junwei Zhang Xing Hu Lingfeng Bao Xin Xia Shanping Li The State Key Laboratory of Blockchain and Data Security Zhejiang University Hangzhou China Software Engineering Application Technology Lab Huawei China
Vulnerabilities are disclosed with corresponding patches so that users can remediate them in time. However, there are instances where patches are not released with the disclosed vulnerabilities, causing hidden dangers... 详细信息
来源: 评论
Distinguishing LLM-generated from Human-written Code by Contrastive Learning
arXiv
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arXiv 2024年
作者: Xu, Xiaodan Ni, Chao Guo, Xinrong Liu, Shaoxuan Wang, Xiaoya Liu, Kui Yang, Xiaohu State Key Laboratory of Blockchain and Data Security Zhejiang University Hangzhou China Software Engineering Application Technology Lab Huawei Hangzhou China
Large language models (LLMs), such as ChatGPT released by OpenAI, have attracted significant attention from both industry and academia due to their demonstrated ability to generate high-quality content for various tas... 详细信息
来源: 评论
Investigating White-Box Attacks for On-Device Models
Investigating White-Box Attacks for On-Device Models
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International Conference on software engineering (ICSE)
作者: Mingyi Zhou Xiang Gao Jing Wu Kui Liu Hailong Sun Li Li Monash University Melbourne VIC Australia Beihang University Beijing China Huawei Software Engineering Application Technology Lab China Beihang University Beijing Yunnan Key Laboratory of Software Engineering China
Numerous mobile apps have leveraged deep learning capabilities. However, on-device models are vulnerable to attacks as they can be easily extracted from their corresponding mobile apps. Although the structure and para... 详细信息
来源: 评论
Investigating White-Box Attacks for On-Device Models
arXiv
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arXiv 2024年
作者: Zhou, Mingyi Liu, Kui Gao, Xiang Sun, Hailong Wu, Jing Li, Li Monash University MelbourneVIC Australia Huawei Software Engineering Application Technology Lab China Beihang University Beijing China Beihang University Beijing Yunnan Key Laboratory of Software Engineering China
Numerous mobile apps have leveraged deep learning capabilities. However, on-device models are vulnerable to attacks as they can be easily extracted from their corresponding mobile apps. Although the structure and para... 详细信息
来源: 评论
Ratchet: Retrieval Augmented Transformer for Program Repair
Ratchet: Retrieval Augmented Transformer for Program Repair
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International Symposium on software Reliability engineering (ISSRE)
作者: Jian Wang Shangqing Liu Xiaofei Xie Jingkai Siow Kui Liu Yi Li Singapore Management University Singapore Nanyang Technological University Singapore Software Engineering Application Technology Laboratory Huawei China
Automated Program Repair (APR) presents the promising momentum of releasing developers from the burden of manual debugging tasks by automatically fixing bugs in various ways. Recent advances in deep learning inspire m...
来源: 评论
Faster or Slower? Performance Mystery of Python Idioms Unveiled with Empirical Evidence
arXiv
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arXiv 2023年
作者: Zhang, Zejun Xing, Zhenchang Xia, Xin Xu, Xiwei Zhu, Liming Lu, Qinghua Australian National University Australia Software Engineering Application Technology Lab Huawei China Data61 CSIRO Australia
The usage of Python idioms is popular among Python developers in a formative study of 101 Python idiom performance related questions on Stack Overflow, we find that developers often get confused about the performance ... 详细信息
来源: 评论
Green Federated Learning over Cloud-RAN with Limited Fronthaul and Quantized Neural Networks  3
Green Federated Learning over Cloud-RAN with Limited Frontha...
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3rd IEEE International Mediterranean Conference on Communications and Networking, MeditCom 2023
作者: Wang, Jiali Mao, Yijie Wang, Ting Shi, Yuanming Shanghai Key Lab. of Trustworthy Computing East China Normal University MoE Engineering Research Center of Software/Hardware Co-Design Technology and Application China China
In this paper, we investigate a green federated learning (FL) framework over cloud radio access network (Cloud-RAN) system that comprises a server, multiple devices and remote radio heads (RRHs). Each device utilizes ... 详细信息
来源: 评论