Search Results - "Ge, Xiuting"

A Systematic Literature Review of Android Malware Detection Using Static Analysis by Pan, Ya, Ge, Xiuting, Fang, Chunrong, Fan, Yong

“…Android malware has been in an increasing trend in recent years due to the pervasiveness of Android operating system. Android malware is installed and run on…”
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Improving actionable warning identification via the refined warning-inducing context representation by Ge, Xiuting, Fang, Chunrong, Li, Xuanye, Zhang, Quanjun, Liu, Jia, Zhao, Zhihong, Chen, Zhenyu

“…Conclusion We improve AWI via the refined warning-inducing context representation, which captures both lexical and structural information for AWI from the…”
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An Empirical Study of Class Rebalancing Methods for Actionable Warning Identification by Ge, Xiuting, Fang, Chunrong, Bai, Tongtong, Liu, Jia, Zhao, Zhihong

“…Actionable warning identification (AWI) is crucial for improving the usability of static analysis tools. Currently, machine learning (ML)-based AWI approaches…”
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Leveraging Android Automated Testing to Assist Crowdsourced Testing by Ge, Xiuting, Yu, Shengcheng, Fang, Chunrong, Zhu, Qi, Zhao, Zhihong

“…Crowdsourced testing is an emerging trend in mobile application testing. The openness of crowdsourced testing provides a promising way to conduct large-scale…”
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Test case classification via few-shot learning by Zhao, Yuan, Liu, Sining, Zhang, Quanjun, Ge, Xiuting, Liu, Jia

“…Crowdsourced testing can reduce testing costs and improve testing efficiency. However, crowdsourced testing generates massive test cases, requiring testers to…”
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An unsupervised feature selection approach for actionable warning identification by Ge, Xiuting, Fang, Chunrong, Liu, Jia, Qing, Mingshuang, Li, Xuanye, Zhao, Zhihong

“…Static Analysis Tools (SATs) are widely applied to detect defects in software projects. However, SATs are overshadowed by a large number of unactionable…”
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Locality-based security bug report identification via active learning by Ge, Xiuting, Fang, Chunrong, Qian, Meiyuan, Ge, Yu, Qing, Mingshuang

“…Security bug report (SBR) identification is a crucial way to eliminate security-critical vulnerabilities during software development. In recent years, many…”
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A Large-Scale Empirical Study of Actionable Warning Distribution within Projects by Ge, Xiuting, Fang, Chunrong, Li, Xuanye, Zheng, Qirui, Liu, Jia, Zhao, Zhihong, Chen, Zhenyu

“…Static Analysis Tools (SATs) show potential defect detection ability while their usability is severely hindered by massive unactionable warnings. To improve…”
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Reducing Label Errors for Actionable Warning Identification by Chen, Haoli, Chen, Xiaocheng, Sun, Xiaolei, Zheng, Qirui, Ge, Xiuting

“…Machine Learning-based Actionable Warning Identification (ML-based AWI) has attracted a great deal of research work in recent years. A reliable warning dataset…”
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CooTest: An Automated Testing Approach for V2X Communication Systems by Guo, An, Gao, Xinyu, Chen, Zhenyu, Xiao, Yuan, Liu, Jiakai, Ge, Xiuting, Sun, Weisong, Fang, Chunrong

“…Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA '24), September 16--20, 2024, Vienna, Austria Perceiving…”
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Impact of datasets on machine learning based methods in Android malware detection: an empirical study by Ge, Xiuting, Huang, Yifan, Hui, Zhanwei, Wang, Xiaojuan, Cao, Xu

“…For Android malware detection, machine learning-based (ML-based) methods show promising performance. However, limited studies are performed to investigate the…”
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AMDroid: Android Malware Detection Using Function Call Graphs by Ge, Xiuting, Pan, Ya, Fan, Yong, Fang, Chunrong

“…With the rapid development of the mobile Internet, Android has been the most popular mobile operating system. Due to the open nature of Android, c countless…”
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Machine Learning for Actionable Warning Identification: A Comprehensive Survey by Ge, Xiuting, Fang, Chunrong, Li, Xuanye, Sun, Weisong, Wu, Daoyuan, Zhai, Juan, Lin, Shangwei, Zhao, Zhihong, Liu, Yang, Chen, Zhenyu

“…Actionable Warning Identification (AWI) plays a crucial role in improving the usability of static code analyzers. With recent advances in Machine Learning…”
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A Survey of Source Code Search: A 3-Dimensional Perspective by Sun, Weisong, Fang, Chunrong, Ge, Yifei, Hu, Yuling, Chen, Yuchen, Zhang, Quanjun, Ge, Xiuting, Liu, Yang, Chen, Zhenyu

“…(Source) code search is widely concerned by software engineering researchers because it can improve the productivity and quality of software development. Given…”
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Pre-trained Model-based Actionable Warning Identification: A Feasibility Study by Ge, Xiuting, Fang, Chunrong, Zhang, Quanjun, Wu, Daoyuan, Yu, Bowen, Zheng, Qirui, Guo, An, Lin, Shangwei, Zhao, Zhihong, Liu, Yang, Chen, Zhenyu

“…Actionable Warning Identification (AWI) plays a pivotal role in improving the usability of static code analyzers. Currently, Machine Learning (ML)-based AWI…”
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Semantic-based false alarm detection approach via machine learning by Qian, Meiyuan, Luo, Jun, Ge, Yu, Sun, Chen, Ge, Xiuting, Huang, Wanmin

“…Many automated vulnerability detection tools are widely used to detect potential security vulnerabilities in software systems. However, these tools suffer from…”
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An Empirical Study on Spectral Clustering-based Software Defect Detection by Qing, Mingshuang, Ge, Xiuting, Hui, ZhanWei, Pan, Ya, Fan, Yong, Wang, Xiaojuan, Cao, Xu

“…Software defect detection is essential in software development. Most existing approaches often apply Supervised Machine Learning (SML) techniques for software…”
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A machine learning-based static analysis warning prioritization by Qing, Mingshuang, Feng, Xiang, Luo, Jun, Huang, Wanmin, Zhang, Jingui, Wang, Ping, Fan, Yong, Ge, Xiuting, Pan, Ya

“…Static analysis tools (SATs) can automatically detect software defects by analyzing the software source code. However, there are a large number of false…”
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