The conference will feature plenary addresses by the following great speakers:
Title: Performance Regression Analysis: Accomplishments and Challenges
Cor-Paul Bezemer is currently a postdoctoral researcher in Software Analysis and Intelligence Lab (SAIL) at Queen’s University in Kingston, Canada. His research interests cover a wide variety of software engineering and performance engineering related topics, including performance regression analysis, performance testing and repository mining. He studied at Delft University of Technology, where he received his BSc (2007), MSc (2009) and PhD (2014) degree in Computer Science.
Title: Mining Bug Repositories
David Lo is an associate professor in School of Information Systems, Singapore Management University, leading the Software Analytics Research (SOAR) group. He received his PhD from School of Computing, National University of Singapore in 2008. Before that, He was studying at School of Computer Engineering, Nanyang Technological University and graduated with a B.Eng (Hons I) in 2004. He is in the editorial board of Empirical Software Engineering, Journal of Software: Evolution and Process, Information Systems, and Neurocomputing (Software Section).
Title: Are Fix-Inducing Changes a Moving Target? A Longitudinal Case Study of Just-In-Time Defect Prediction
Shane McIntosh is an assistant professor in the Software Repository Excavation and Build Engineering Labs (REBELs) at McGill University. He received his PhD from in Software Analysis and Intelligence Lab (SAIL) at Queen’s University in Kingston, Canada. He is performing empirical studies that mine the historical data that is generated during the development of large-scale software systems. His research focuses on release engineering and software quality.
Title: Software Defect Prediction: Trends and Challenges
Jaechang Nam is currently a postdoctoral fellow working in Prof. Lin Tan’s research group. He received his PhD from in Computer Science and Engineering at The Hong Kong University of Science and Technology, Hong Kong. His research interests include Software Quality Prediction, Transfer Learning in Software Engineering, Software Repository Mining, Empirical Software Engineering, Software Engineering in Health.