刘        超： liu.chao@cqu.edu.cn

    研究方向：大数据与软件智能、人工智能、自然语言处理

    联系地址：重庆大学虎溪校区信息大楼802室

刘超，博士，重庆大学大数据与软件学院副教授，硕士生导师；信息物理社会可信计算（CPS）教育部重点实验室，大数据智能研究所骨干；中国计算机学会CCF执行委员；主要从事大数据智能、智能软件工程、软件解析等方面的研究，近年来主要研究大规模代码搜索、代码大模型、代码解析、软件复用、软件可视化等；目前发表学术论文20余篇，包括领域顶级期刊/会议（CSUR, TOSEM, TSC, ICSE, FSE, ISSTA）以及领域权威期刊/会议（IST, JSS, ICPC, SANER, COMPSAC, InternetWare）。

学习/工作经历

2021/10-至       今 重庆大学，大数据与软件学院，教师

2019/03-2021/09 浙江大学，计算机科学与技术学院，博士后

2019/10-2021/09 鹏城实验室，分布式高性能软件院士工作室，助理研究员

2019/10-2020/10 阿里巴巴，研发效能事业部，访问学者 

2018/12-2019/01 上海百度，工程效率部，访问学者

2007/09-2018/12 重庆大学，大数据与软件学院，学士/硕士/博士

科研项目                                       

2023-2026 重庆市人工智能重大专项项目, 多模态生成大模型关键技术研发及应用, 参与

2022-2025 重庆市技术创新与应用发展专项重点项目, 价值流驱动的软件研发效能提升智能服务平台研发与应用, 参与

2023-2025 国家自然科学基金青年基金，面向大规模代码搜索的复杂语义映射模型研究，主持

2022-2024 中国博士后科学基金面上资助，基于层次化语义融合的深度代码搜索方法研究，主持

2022-2024 重庆市博士后出站来渝资助，数据驱动的智能代码推荐技术，主持

2018-2021 国家重点研发计划子课题，基于代码大数据的程序语义学习与现场大数据生成技术，参与

2019-2020 企事业单位委托科技项目（阿里），代码推荐技术，参与

2011-2012 国家863项目子课题，三峡库区城市水环境项目的知识管理与成果扩散，参与

研究论文                                         

• 2024. Chao Liu, Xindong Zhang, Hongyu Zhang, Zhiyuan Wan, Zhan Huang, Meng Yan. An Empirical Study of Code Search in Intelligent Coding Assistant: Perceptions, Expectations, and Directions. FSE (CCF-A).

• 2024. Dong Li, Meng Yan, Yaosheng Zhang, Zhongxin Liu, Chao Liu, Xiaohong Zhang, Ting Chen, David Lo. CoSec: On-the-Fly Security Hardening of Code LLMs via Supervised Co-Decoding. ISSTA (CCF-A).
  

• 2024. Xiaoqi Yue, Chao Liu, Neng Zhang, Haibo Hu, Xiaohong Zhang. VisRepo: A Visual Retrieval Tool for Large-Scale Open-Source Projects. InternetWare (CCF-C).  

• 2024. Ying Fu, Meng Yan, Pinjia He, Chao Liu, Xiaohong Zhang, Dan Yang. End-to-end log statement generation at block-level. JSS (CCF-B).

• 2024. Desheng Sun, Xiaoqi Yue, Chao Liu, Hongxing Qin, Haibo Hu. SFLVis: visual analysis of software fault localization. Journal of Visualization.

• 2024. Huanhuan Yang, Ling Xu, Chao Liu, Luwen Huangfu. Query-oriented two-stage attention-based model for code search. JSS (CCF-B).

• 2024. Xiaoqi Yue, Dan Feng, Desheng Sun, Chao Liu, Hongxing Qin, Haibo Hu. AirPollutionViz: visual analytics for understanding the spatio-temporal evolution of air pollution. Journal of Visualization. 

• 2024. Chao Liu, Xuanlin Bao, Hongyu Zhang, Neng Zhang, Haibo Hu, Xiaohong Zhang, Meng Yan. Guiding ChatGPT for Better Code Generation: An Empirical Study. IST (CCF-B) . 

• 2024. Chao Liu, Runfeng Cai, Yiqun Zhou, Xin Chen, Haibo Hu, Meng Yan. Understanding the implementation issues when using deep learning frameworks. IST (CCF-B). 

• 2024. Zhongyang Deng, Ling Xu, Chao Liu, Luwen Huangfu, Meng Yan. Code semantic enrichment for deep code search. JSS (CCF-B). 

• 2023. Zhongqi Chen, Neng Zhang, Pengyue Si, Qinde Chen, Chao Liu, Zibin Zheng. ShellFusion: An Answer Generator for Shell Programming Tasks via Knowledge Fusion. ICSE (CCF-A). Tool Demo.

• 2022. Chao Liu, Xuanlin Bao, Xin Xia, Meng Yan, David Lo, Ting Zhang. CodeMatcher: A Tool for Large-Scale Code Search Based on Query Semantics Matching. FSE (CCF-A). Tool Demo.
  

• 2022. Neng Zhang, Chao Liu, Xin Xia, Christoph Treude, Ying Zou, David Lo, Zibin Zheng. ShellFusion: Answer Generation for Shell Programming Tasks via Knowledge Fusion. ICSE (CCF-A).

• 2022. Zhongyang Deng, Ling Xu, Chao Liu, Meng Yan, Zhou Xu, Yan Lei. Fine-Grained Co-Attentive Representation Learning for Semantic Code Search. SANER (CCF-B).

• 2021. Chao Liu, Xin Xia, David Lo, Cuiyun Gao, Xiaohu Yang, John Grundy. Opportunities and Challenges in Code Search Tools. CSUR (SCI-1).

• 2021. Chao Liu, Xin Xia, David Lo, Zhiwei Liu, Ahmed E Hassan, Shanping Li. CodeMatcher: Searching Code Based on Sequential Semantics of Important Query Words. TOSEM (CCF-A). Invited to ICSE'2022 (CCF-A).

• 2021. Chao Liu, Cuiyun Gao, Xin Xia, David Lo, John Grundy, Xiaohu Yang. On the Reproducibility and Replicability of Deep Learning in Software Engineering. TOSEM (CCF-A).

• 2021. Ling Xu, Huanhuan Yang, Chao Liu, Jianhang Shuai, Meng Yan, Yan Lei and Zhou Xu. Two-Stage Attention-Based Model for Code Search with Textual and Structural Features. SANER (CCF-B).

• 2020. Jianhang Shuai, Ling Xu, Chao Liu, Meng Yan, Xin Xia, Yan Lei. Improving Code Search with Co-Attentive Representation Learning. ICPC (CCF-B).

• 2020. Bei Wang, Ling Xu, Meng Yan, Chao Liu, Ling Liu. Multi-Dimension Convolutional Neural Network for Bug Localization. TSC (CCF-B).

• 2020. Chao Liu, Li Fu, Dan Yang, David R Miller, Junming Wang. Non-Gaussian Lagrangian Stochastic Model for Wind Field Simulation in the Surface Layer. AAS (SCI-2).

• 2019. Chao Liu, Dan Yang, Xin Xia, Meng Yan, Xiaohong Zhang. A Two-Phase Transfer Learning Model for Cross-Project Defect Prediction. IST (CCF-B).

• 2018. Chao Liu, Dan Yang, Xin Xia, Meng Yan, Xiaohong Zhang. Cross-Project Change-Proneness Prediction. COMPSAC (CCF-C).

• 2018. Yongxin Ge, Min Chen, Chao Liu*, Feiyi Chen, Sheng Huang, Hongxing Wang. Deep Metric Learning for software Change-Proneness Prediction. IScIDE (EI).

• 2018. Chao Liu, Dan Yang, Xiaohong Zhang, Haibo Hu, Jed Barson, Baishakhi Ray. A Recommender System for Developer Onboarding. ICSE (CCF-A), Poster Track.

• 2018. Chao Liu, Dan Yang, Xiaohong Zhang, Baishakhi Ray, Md Masudur Rahman. Recommending GitHub Projects for Developer Onboarding. Access (SCI-2).

• 2017. Meng Yan, Xiaohong Zhang, Chao Liu, Ling Xu, Mengning Yang, Dan Yang. Automated Change-Prone Class Prediction on Unlabeled Dataset Using Unsupervised Method. IST (CCF-B).
  

• 2017. Meng Yan, Xiaohong Zhang, Chao Liu, Jie Zou, Ling Xu, Xin Xia. Learning to Aggregate: An Automated Aggregation Method for Software Quality Model. ICSE (CCF-A). Poster Track.

• 2016. Meng Yan, Mengning Yang, Chao Liu, Xiaohong Zhang. Self-Learning Change-Prone Class Prediction. SEKE (CCF-C).