Software Analytics focuses on utilizing data-driven approaches to help improve the quality of software systems, the user experience of interacting with software systems, and the productivity of software development process. Software Analytics is an important research area in the software engineering community for more than a decade. It has already made broad impact in software industry. As the computing paradigm was shifting towards cloud computing, we started to focus our Software Analytics research on cloud computing and created the research topic Cloud Intelligence. Cloud Intelligence targets at utilizing AI/ML technologies to help design, build, and operate high-quality and high-efficiency cloud systems at scale. Due to the distributed nature, great complexity, and enormous scale of cloud systems, Cloud Intelligence presents unique challenges and opportunities to the Software Analytics research. In this talk, I will first introduce the research landscape of software analytics and Cloud Intelligence. Then using a couple of projects as examples, I will talk about our research on Cloud Intelligence and its impact, as well as the research challenges and opportunities in Cloud Intelligence moving forward.

Dr. Dongmei Zhang is the Assistant Managing Director of Microsoft Research Asia (MSRA), leading the research of Data, Knowledge and Intelligence (DKI) which is an interdisciplinary area across data intelligence, knowledge computing, information visualization, and software engineering. Dr. Zhang founded the Software Analytics Group in MSRA in 2009. Since then she has been leading the group to research software analytics technologies. In addition to conducting state-of-the-art research, her group collaborates closely with multiple product teams in Microsoft, and has developed and deployed software analytics tools that have created high business impact. In recent years, Dr. Zhang and her teams have expanded the impact into the business intelligence area, and helped Microsoft establish technology leadership in the direction of Smart Data Discovery.