Singapore Management University
Bugs are prevalent in software systems. Needless to say, these bugs need to be identified, managed and fixed to improve software quality and increase customer satisfaction. Unfortunately, these tasks are non-trivial; many bugs remain hidden and unresolved for weeks (or even years!). Can AI help? Of course! AI can be trained on rich historical data to allow it to mimic developers in squashing bugs (and more!). For AI to work well, it often needs to be trained on a sizable amount of data. Fortunately, many projects maintain large historical data in various repositories that are publicly available. Although full automation is not feasible yet (at least in the general sense), AI-infused solutions can support developers in their quest to identify, manage, and fix bugs (and thus remaining successful despite living with bugs). This talk will provide an overview and reflection of the large body of work that builds automated tools that leverage the power of AI, trained on rich data in various repositories, for various tasks in the bug identification and resolution process. Some open challenges will also be presented, with the goal of encouraging more research in this exciting area in the intersection of Software Engineering and AI.
David Lo is an ACM Distinguished Member (Scientist) and Professor of Computer Science at Singapore Management University, leading the Software Analytics Research (SOAR) group. His research interest is in the intersection of software engineering, cybersecurity, and data science, encompassing socio-technical aspects and analysis of different kinds of software artifacts, with the goal of improving software quality and security and developer productivity. His work has been published in major and premier conferences and journals in the area of software engineering, AI, and cybersecurity attracting substantial interest from the community. He has won more than 15 international research and service awards including 6 ACM SIGSOFT Distinguished Paper awards. He has served in more than 30 organizing committees and many program committees of research conferences, including serving as general or program co-chairs of ASE 2020, SANER 2019, ICSME 2018, ICPC 2017, and ASE 2016. He is also serving on the editorial board of a number of journals including Journal of Software Engineering Research and Development, IEEE Transactions on Software Engineering, Empirical Software Engineering, and IEEE Transactions on Reliability. His former PhD students, trainees, and postdocs have secured faculty positions and employment at high-tech industries around the globe. More information about him and his research group are available at http://www.mysmu.edu/faculty/davidlo/ and https://soarsmu.github.io/.