Recommendation Systems in Software Engineering

Martin P. Robillard is an Associate Professor of Computer Science at McGill University. His current research focuses on problems related to API usability, information discovery and knowledge management in software engineering.Walid Maalej is a Professor of Informatics at the University of Hamburg. He previously led a research group on human and context factors in software at the TU Munich. His current research interests include the context-aware recommendation systems and social software engineering.Robert J. Walker is an Associate Professor of Computer Science at the University of Calgary. His current research involves automated analysis and support for unanticipated software reuse tasks.Thomas Zimmermann is a researcher at Microsoft Research, Adjunct Assistant Professor at the University of Calgary and an affiliate faculty member at the University of Washington. He is best known for his research on systematic mining of version archives and bug databases to conduct empirical studies and to build tools.

"The book is a perfect starting point of study for graduate students of software engineering, especially when specializing in recommendation. It is highly recommended also to software professionals seeking to learn what are the possible future directions of their professional field. The book is impressive. [...] I highly recommend this book to software engineering students, professionals, experts, and other interested readers." P. Navrat, ACM Computing Reviews, November 2014

• 1 An Introduction to Recommendation Systems in Software Engineering.- Part I Techniques.- 2 Basic Approaches in Recommendation Systems.- 3 Data Mining.- 4 Recommendation Systems in-the-Small.- 5 Source Code Based Recommendation Systems.- 6 Mining Bug Data.- 7 Collecting and Processing Interaction Data for Recommendation Systems.- 8 Developer Profiles for Recommendation Systems.- 9 Recommendation Delivery.- Part II Evaluation.- 10 Dimensions and Metrics for Evaluating Recommendation Systems.- 11 Benchmarking.- 12 Simulation.- 13 Field Studies.- Part III Applications.- 14 Reuse-Oriented Code Recommendation Systems.- 15 Recommending Refactoring Operations in Large Software Systems.- 16 Recommending Program Transformations.- 17 Recommendation Systems in Requirements Discovery.- 18 Changes, Evolution and Bugs.- 19 Recommendation Heuristics for Improving Product Line Configuration Processes.