时间：2016年6月3日（周五）下午14：30
地点：旗山校区软件学院507报告厅
主讲：David LO（School of Information System, Singapore Management University, Associate Professor）
主办：软件学院
专家简介：David Lo is an associate professor in School of Information Systems, Singapore Management University, working in the intersection of software engineering and data mining research. He is a leading researcher in the emerging field of software analytics having published more than a hundred papers on the topic in top/major software engineering/data mining conferences/journals and delivered invited keynote speeches and lectures on the topic in many venues. He received the Lee Foundation Fellow for Research Excellence and has won a number of international research awards including two ACM SIGSOFT distinguished paper awards. He has served in the organizing and program committees of many top/major software engineering and data mining conferences including ICSE, ASE, and KDD. He currently serves in the steering committee of the International Conference on Software ANalysis, Evolution and Reengineering (SANER), and is an editorial board member of the Empirical Software Engineering and Neurocomputing journals. He is also serving as the general chair of the 31st IEEE/ACM International Conference on Automated Software Engineering (ASE 2016), and the program co-chair of the 25th IEEE International Conference on Program Comprehension (ICPC 2017).
报告摘要：Software engineering is in a belle époque of analytics. During the process of engineering software systems, software developers and stakeholders generate a large amount of data and artefacts, be it requirement documents, design diagrams, bug reports, source code files, commit logs, and many more, that can be automatically analysed to improve and automate software development, testing, and maintenance efforts. Software analytics, which focuses on the design and development of specialized data analysis techniques to solve software engineering problems, is an emerging sub-field of software engineering and data mining with many applications. This talk discusses the various scenarios for which software analytics can help developers in performing various software engineering tasks. In particular, we will discuss the various ways software analytics can help in coding and collaboration, testing and debugging, and requirement and design validation. Future challenges and opportunities for software analytics in the era of software engineering big data will also be discussed.