讲座题目：Bridging the Gap between AI and SE
夏鑫，博士，澳大利亚蒙纳士大学ARC DECRA Fellow和讲师，研究方向为软件仓库挖掘和软件解析学。夏鑫至今发表了151篇期刊和会议论文，其中包括33篇CCF A类期刊和会议长文（包括17篇TSE，8篇ASE），57篇CCF B类期刊和会议长文。部分论文获得国际会议最佳/杰出论文奖项，包括3篇ACM SIGSOFT Distinguished Paper Award（ASE 2018和2019， ICPC 2018），ESEC/FSE 2019 Best Tool Demo Award。此外他担任了MSR和SANER会议的Steering Committee，多个国际会 议的PC (ICSE，ESEC/FSE, ASE等)，以及参与组织了多个国际会议（ASE 2020，ICSME 2020, SANER 2019等）。更多信息在https://xin-xia.github.io/。
Today, data miners often apply or extend AI techniques to solve problems across many domains (e.g., social media, health informatics, and software systems); while domain experts leverage their own domain knowledge to solve their own problems. Data miners often apply their automated techniques to solve a wide range of problems across different domains with limited knowledge of the domain; while domain experts often have limited knowledge of automated techniques when solving their domain-specific problems. My research tries to bridge the gap between both types of experts (i.e., Data miners and Domain Experts). In this talk, I will focus on the software engineering domain and I will give an overview of several challenges facing data miner and domain experts as they make use of automated techniques, in particular:
(1) strong performance of techniques is not sufficient, instead a deeper understanding of the domain is essential;
(2) results should be presented in a domain-centric context; (3) an easy approach might perform better than a complex approach. I will present examples from my research to explain what these challenges are, why do they appear, and my efforts to avoid them.