Call for Chapters
Recommendation Systems in Software Engineering
A book to be published by Springer and edited by:
Martin P. Robillard, McGill University (Canada)
Walid Maalej, University of Hamburg (Germany)
Robert J. Walker, University of Calgary (Canada)
Thomas Zimmermann, Microsoft Research (USA)
Chapter contributors will be invited to a 2-day workshop in Germany in April 2013.
Recommendation systems support decision making by helping their users navigate through large information spaces. Many activities in software engineering require searching, understanding, and managing large amounts of highly-technical and inter-related information.
With the growth of public and private data stores and the emergence of off-the-shelf data-mining technology, recommendations systems have emerged that specifically target the unique challenges of navigating software engineering data.
This book will collect state-of-the-art knowledge on the basic techniques required to mine software engineering data to produce recommendations, on the best way to apply these techniques effectively in various application domains, and on the approaches that can be employed to assess the value of recommendations in software engineering.
We invite proposals for chapters that synthesize existing knowledge on relevant background topics and application areas for recommendation systems. Chapters should be accessible to senior undergraduate students and graduate students with a background in Computer Science, Software Engineering, or related disciplines. Chapters are not expected to correspond to the description of a single research project or technique. The proposed Table of Contents offers suggestions for target topics.
TABLE OF CONTENTS (Tentative)
Chapter 1: Introduction
Part I: Techniques
This section will provide a coherent and complete treatment of techniques to collect and process software engineering data that can be used to produce recommendations in SE.
Chapter: Basic approaches in recommendation systems
Chapter: Data mining techniques in software engineering
Chapter: Mining source code for recommendation systems
Chapter: Mining software evolution data for recommendation systems
Chapter: Natural language processing for recommendation systems
Chapter: Recommendations without data mining: small data and heuristics
Chapter: Code synthesis
Chapter: Collecting and processing interaction data
Chapter: User models, feedback, and social involvement
Part II: Evaluation
Techniques and experimental designs to evaluate recommendations.
Chapter: User studies
Chapter: Field studies
Part III: Applications
Descriptions of the needs and issues involved in entire systems for specific applications, focusing on the engineering insights required to make effective recommendation. Minimalist discussion of the evaluation.
Chapter: Changes and Evolution
Chapter: Productivity, coordination, and management
Chapter: People, collaboration, and knowledge sharing
Part IV: The Road Ahead
Chapter: Outstanding issues to be addressed
PROCESS AND IMPORTANT DATES
To submit a chapter proposal, please submit a detailed abstract (text only) presenting an overview of the proposed content, to Easychair
To submit, enter the required information, the overview of the proposed content in the "abstract" field, and select the "abstract only" check-box.
Proposals will be reviewed by the four co-editors. The authors participating in this book project will also be asked to review chapters by other contributors, and will be invited to an editing workshop to unify the presentation and content. The workshop is planned for April 2013 in Germany.
- Intent of Submission: 15 October 2012
- Initial Chapter Submission: 31 January 2013
- Chapter Reviews Submitted: 31 March 2013
- Editing Workshop: April 2013
- Final Submission to Editors: 7 June 2013
- Camera Ready Submission: 15 July 2013
For any inquiries please contact:
School of Computer Science