Ayșe Tosun

Abstract The tutorial will share our experience and views on software data analytics in practice with a retrospect to our previous work as well as examples from the current work. Data science involves putting together an interdisciplinary team of experts and one of the critical success factors is that it should follow a due process in conducting analytics and using machine learning techniques. A blueprint of data science projects in practice will be discussed as the methodology used in Data Science Lab (DSL) to explain the process. Over 15 years of joint research projects with the industry, we have encountered similar data analytics patterns in diverse organizations and in different problem cases. In the tutorial, we will discuss these patterns following a `software analytics' framework: problem identification, data collection, descriptive statistics and decision making.

Speaker's Bio Dr. Ayse Tosun is an assistant professor at Faculty of Computer and Informatics, Istanbul Technical University (ITU), Istanbul, Turkey. Prior to joining ITU, she worked as a post-doctoral research fellow at Department of Information Processing Science, University of Oulu, Finland. She received her PhD in 2012, and MSc degree in 2008 from Department of Computer Engineering, Bogazici University, Turkey. Her research interests are empirical software engineering, more specifically mining software data repositories, software measurement, software process improvement, software quality prediction models, and applications of AI on building recommendation systems for software engineering.