报告题目1：Mining Bug Repositories
报告人：David Lo 教授
报告人单位： Singapore Management University
David Lo is an Associate Professor in School of Information Systems, Singapore Management University. He is working in the intersection of software engineering and data mining research. He is an active researcher in the emerging field of software analytics that focuses on the design and development of specialized data analysis techniques to solve software engineering problems. He has received a number of international awards including two ACM distinguished paper awards. He has contributed as an organizing committee member of many conferences; the upcoming ones include serving as a program co-chair of the 34th IEEE International Conference on Software Maintenance and Evolution (ICSME’18) and workshop co-chair of the 41st ACM/IEEE International Conference on Software Engineering (ICSE’19). He serves/served in the steering committee of the IEEE International Conference on Software ANalysis, Evolution and Reengineering (SANER), IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM), and IEEE/ACM International Conference on Automated Software Engineering (ASE). He is an editorial board member of Empirical Software Engineering, Journal of Software: Evolution and Process, Information and Software Technology, Information Systems, and Neurocomputing. For more information, please visit: http://www.mysmu.edu/faculty/davidlo/
Many software systems receive hundreds of bug reports daily, which is often too many for developers to handle. Even for a single bug report, resolving it can be a costly process that consumes much of developers’ time and energy. To deal with these challenges, automated methods that can help developers manage bug reports are needed. In this talk, I will share work done by the Software Analytics Research group (SOAR) in Singapore Management University (SMU) on mining bug repositories to automate various bug report management tasks. This talk will especially focus on two of our recent work: (1) a recommendation system that assigns bug reports to suitable developers by integrating activity- and location-based information in a learning to rank framework, and (2) a solution that repairs buggy code by automatically constructing and leveraging a knowledge base built by mining a large number of historical bug fixes.
邀请人： 刘进 教授、玄跻峰 教授、谢晓园 教授