相关论文发表
2024年&CCF-A类
InterpretARA: Enhancing Hybrid Automatic Readability Assessment with Linguistic Feature Interpreter and Contrastive LearningJinshan Zeng, Xianchao Tong, Xianglong Yu, Wenyan Xiao, Qing Huang*
In the Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI-24), 2024.2.22-2024.2.25, Vancouver, British Columbia at the Vancouver Convention Centre-West Building.2024.3.24,38(17), 19497-19505.
2024年&CCF-A类
Enhancing Exploratory Testing by Large Language Model and Knowledge GraphYanqi Su, Dianshu Liao, Zhenchang Xing, Qing Huang*, Mulong Xie, Qinghua Lu, Xiwei Xu
In 46th International Conference on Software Engineering, ICSE 2024. 会议时间 2024.4.14-2024.4.20, 发表时间 2023.12.15, Lisbon, Rortuga, Article 98, 1-12.
2023年&CCF-A类
Answering Uncertain, Under-Specified API Queries Assisted by Knowledge-Aware Human-AI DialogueQing Huang, Zishuai Li, Zhenchang Xing, Zhengkang Zuo*, Xin Peng, Xiwei Xu, Qinghua Lu
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 2023.12.25, 50(2): 1 (CCF-A, SCI一区，影响因子7.4 )
点击查看宣传海报
2023年&CCF-A类
Prompt Sapper: A LLM-Empowered Production Tool for Building AI ChainsYu Cheng, Jieshan Chen, Qing Huang, Zhenchang Xing; Xiwei Xu, Qinghua Lu
ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY, 1, 1 (December.3 2023), 31 pages. (CCF-A, SCI一区，影响因子3.685 )
点击查看宣传海报
2023年&CCF-A类
FQN Inference in Partial Code by Prompt-tuned Language Model of CodeQing Huang, Zhiqiang Yuan, Zhenchang Xing; Xin Peng, Xiwei Xu, Qinghua Lu.
ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY, 2023.8.24, 33 (2), 31:1-31:32. (CCF-A, SCI一区，影响因子3.685 ).
点击查看宣传海报
2023年&CCF-A类
Let's Chat to Find the APIs: Connecting Human, LLM and Knowledge Graph through AI ChainQing Huang, Zhenyu Wan, Zhenchang Xing, Changjing Wang, Jieshan Chen, Xiwei Xu and Qinghua Lu.
ASE 2023顶会报告
点击查看宣传海报
2023年&CCF-A类
API Entity and Relation Joint Extraction from Text via Dynamic Prompt-tuned Language ModelQing Huang, Yanbang Sun, Zhenchang Xing, Min Yu, Xiwei Xu, Qinghua Lu
ACM Transactions on Software Engineering and Methodology(CCF-A, SCI一区，影响因子3.685 )
点击查看宣传海报
2023年&CCF-A类
Semantic-enriched Code Knowledge Graph to Reveal Unknowns in Smart Contract Code ReuseQing Huang , Dianshu Liao , Zhenchang Xing , Zhengkang Zuo , Changjing Wang , Xin Xia.
ACM Transactions on Software Engineering and Methodology(CCF-A, SCI一区，影响因子3.685 )
点击查看宣传海报
点击查看成果演示
2022年&CCF-A类
PCR-Chain: Partial Code Reuse Assisted by Hierarchical Chaining of Prompts on Frozen CopilotQing Huang, Jiahui Zhu, Zhilong Li, Zhenchang Xing, Changjing Wang, Xiwei Xu.
Proceedings of the ACM/IEEE 45th International Conference on Software Engineering: Companion Proceedings.
点击查看宣传海报
点击查看ICSE 2023顶会报告
2022年&CCF-A类
Prompt-tuned Code Language Model as a Neural Knowledge Base for Type Inference in Statically-Typed Partial CodeQing Huang, Zhiqiang Yuan, Zhenchang Xing, Xiwei Xu, Liming Zhu, Qinghua Lu
37th IEEE/ACM International Conference on Automated Software Engineering
点击查看宣传海报
点击查看ASE 2022顶会报告
2022年&CCF-A类
1+1>2: Programming Know-What and Know-How Knowledge Fusion, Semantic Enrichment and Coherent Application
Qing Huang, Zhiqiang Yuan, Zhenchang Xing, Zhengkang Zuo, Changjing Wang, Xin Xia
IEEE Transactions on Services Computing(CCF-A, SCI二区，影响因子11.019 )
点击查看宣传海报
点击查看TSC顶刊报告
2019年&CCF-A类
QE-integrating framework based on Github knowledge and SVM ranking
Q Huang, H Wu
Science China Information Sciences 62, 1-16(CCF-A, SCI 二区，影响因子7.275)
相关基金
1.可解释的图神经网络程序语义表示方法研究，国家自然科学基金地区项目，62262031，34万，2023.1.1-2026.12.31，主持，在研.
2.基于演化数据语义理解的多元扩展代码搜索方法研究，国家自然科学基金青年项目，61902162，26万，2020.1.1-2022.12.31，主持，结题.
3.基于源代码演化数据的程序语义表示方法研究，江西省自然科学基金面上项目，20202BAB202015，6万，2020.1.1-2022.12.31，主持，结题.
4.基于开源群智的程序演化语义表示及代码搜索技术研究，国家留学基金委2020年面上项目，澳大利亚国立大学，访问学者，CSC NO. 202008360093, 2020.4,2020.12.31-2021.12.31.
创新项目
1.2022年研究生省级创新项目，基于小样本提示学习的数据类型推理，袁志强。
2.2021年研究生省级创新项目，基于API和TASK多源数据的知识融合与知识发现研究，罗智文。
3.2023年研究生省级创新项目，基于上下文学习的分层提示链的片段代码重用，朱家辉。
4.2023年研究生省级创新项目，基于AI Chain的控制流图生成研究，邹舟。
5.2023年研究生省级创新项目，基于动态提示学习的 API 实体关系联合提取，李志龙。
学生风采
本科生廖滇书围绕代码推荐和代码检测向知名企业做研究报告
本科生挑战杯作品【面向海量代码片段的完整数据类型推理关键技术研究及基于该技术的“双料”插件开发（江西省二等奖）】作品介绍
本科生挑战杯作品【知识图谱间知识融合和语义强化的关键技术研究及基于该技术的API联合知识搜索引擎】作品介绍
硕士生李子帅围绕AI结对编程所做的技术分享报告。
硕士生孙彦帮围绕软件编程知识提取所做的技术分享报告。
硕士生李志龙、邹舟和朱家辉围绕新一代编程范型所做的技术分享报告。