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E-raamat: Recommendation Systems in Software Engineering

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  • Formaat: PDF+DRM
  • Ilmumisaeg: 30-Apr-2014
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Keel: eng
  • ISBN-13: 9783642451355
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  • Formaat: PDF+DRM
  • Ilmumisaeg: 30-Apr-2014
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Keel: eng
  • ISBN-13: 9783642451355

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With the growth of public and private data stores and the emergence of off-the-shelf data-mining technology, recommendation systems have emerged that specifically address the unique challenges of navigating and interpreting software engineering data.

This book collects, structures and formalizes knowledge on recommendation systems in software engineering. It adopts a pragmatic approach with an explicit focus on system design, implementation, and evaluation. The book is divided into three parts: “Part I – Techniques” introduces basics for building recommenders in software engineering, including techniques for collecting and processing software engineering data, but also for presenting recommendations to users as part of their workflow. “Part II – Evaluation” summarizes methods and experimental designs for evaluating recommendations in software engineering. “Part III – Applications” describes needs, issues and solution concepts involved in entire recommendation systems for specific software engineering tasks, focusing on the engineering insights required to make effective recommendations. The book is complemented by the webpage rsse.org/book, which includes free supplemental materials for readers of this book and anyone interested in recommendation systems in software engineering, including lecture slides, data sets, source code, and an overview of people, groups, papers and tools with regard to recommendation systems in software engineering.

The book is particularly well-suited for graduate students and researchers building new recommendation systems for software engineering applications or in other high-tech fields. It may also serve as the basis for graduate courses on recommendation systems, applied data mining or software engineering. Software engineering practitioners developing recommendation systems or similar applications with predictive functionality will also benefit from the broad spectrum of topics covered.



This book surveys and analyzes information on recommendation systems in software engineering, in separate sections on Techniques, Evaluation and Applications. A supplemental website offers additional material, including lecture slides, source code and more.

Arvustused

"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
1(14)
Martin P. Robillard
Robert J. Walker
Part I Techniques
2 Basic Approaches in Recommendation Systems
15(24)
Alexander Felfernig
Michael Jeran
Gerald Ninaus
Florian Reinfrank
Stefan Reiterer
Martin Stettinger
3 Data Mining
39(38)
Tim Menzies
4 Recommendation Systems in-the-Small
77(16)
Laura Inozemtseva
Reid Holmes
Robert J. Walker
5 Source Code-Based Recommendation Systems
93(38)
Kim Mens
Angela Lozano
6 Mining Bug Data
131(42)
Kim Herzig
Andreas Zeller
7 Collecting and Processing Interaction Data for Recommendation Systems
173(26)
Walid Maalej
Thomas Fritz
Romain Robbes
8 Developer Profiles for Recommendation Systems
199(24)
Annie T.T. Ying
Martin P. Robillard
9 Recommendation Delivery
223(22)
Emerson Murphy-Hill
Gail C. Murphy
Part II Evaluation
10 Dimensions and Metrics for Evaluating Recommendation Systems
245(30)
Iman Avazpour
Teerat Pitakrat
Lars Grunske
John Grundy
11 Benchmarking
275(26)
Alan Said
Domonkos Tikk
Paolo Cremonesi
12 Simulation
301(28)
Robert J. Walker
Reid Holmes
13 Field Studies
329(30)
Ayse Tosun Misirli
Ayse Bener
Bora Caglayan
Gul Calikli
Burak Turhan
Part III Applications
14 Reuse-Oriented Code Recommendation Systems
359(28)
Werner Janjic
Oliver Hummel
Colin Atkinson
15 Recommending Refactoring Operations in Large Software Systems
387(34)
Gabriele Bavota
Andrea De Lucia
Andrian Marcus
Rocco Oliveto
16 Recommending Program Transformations
421(34)
Miryung Kim
Na Meng
17 Recommendation Systems in Requirements Discovery
455(22)
Negar Hariri
Carlos Castro-Herrera
Jane Cleland-Huang
Bamshad Mobasher
18 Changes, Evolution, and Bugs
477(34)
Markus Borg
Per Runeson
19 Recommendation Heuristics for Improving Product Line Configuration Processes
511(28)
Raul Mazo
Cosmin Dumitrescu
Camille Salinesi
Daniel Diaz
Glossary 539(16)
Index 555
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.