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International Symposium on System and Software Reliability (ISSSR)

作者： Liang Luo Assistant Director of National & Local Joint Engineering Lab of Next Generation Internet Data Processing Technology School of Computer Science and Engineering (School of Cyberspace Security) University of Electronic Science and Technology of China

ISBN: (数字)9781665453974

ISBN: (纸本)9781665453981

Human-Machine-Environment (HME) Tri-Co (Coexisting, Cooperative, Cognitive) Education is an indispensable prerequisite and the main content of Artificial Intelligence empowering junior science education. Moreover, it is also a critical requirement for improving the quality of education and promoting the high-end development of education information. Building a unique learning environment with scene perception and an intelligent cognitive process is a tremendous challenge for diverse needs in junior scientific learning scenarios. Therefore, it is necessary to study human-machine cooperation scenarios and design advanced software and hardware. This talk will introduce some of our recent work in affective analysis, multimodal affection data processing methods, and reliability and security of affective computing systems, etc. We will also discuss some directions that are worthy of further studies.

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A prototype for software refactoring recommendation system

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International Journal of Performability engineering 2020年第7期16卷 1095-1104页

作者： Gao, Yuan Zhang, Youchun Lu, Wenpeng Luo, Jie Hao, Daqing China National-Local Joint Engineering Lab of Next Generation Internet Data Processing Technology University of Electronic Science and Technology of China Chengdu610054 China China School of Computer Science and Technology Qilu University of Technology Shandong Academy of Sciences Jinan250353 China State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Beijing100191 China Luoyang Bearing Research Institute Co. Ltd. Luoyang471039 China

Software refactoring is used to reduce the costs and risks of software evolution. Automated software refactoring tools can reduce risks caused by manual refactoring, improve efficiency, and reduce difficulties of software refactoring. Researchers have made great efforts to research how to implement and improve automated software refactoring tools. However, results of automated refactoring tools often deviate from the intentions of the implementer. To this end, in this paper, we proposed and implemented a prototype tool for a software refactoring recommendation system based on previous research. The tool provides users with an optimized software refactoring scheme and users realize refactoring intentions by interacting with the tool. The tool has been evaluated to be effective, especially for users who are inexperienced and non- English speaking. © 2020 Totem Publisher, Inc. All rights reserved.

关键词： Recommender systems

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