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1. RSSE@SIGSOFT FSE 2008: Atlanta, GA, USA
- Proceedings of the 2008 International Workshop on Recommendation Systems for Software Engineering, RSSE 2008, Atlanta, GA, USA, November 9, 2008. ACM 2008, ISBN 978-1-60558-228-3
Long talks
- Beat Fluri, Jonas Zuberbühler, Harald C. Gall
:
Recommending method invocation context changes. 1-5 - Segla Kpodjedo, Filippo Ricca, Philippe Galinier, Giuliano Antoniol:
Not all classes are created equal: toward a recommendation system for focusing testing. 6-10 - Hans-Jörg Happel, Walid Maalej:
Potentials and challenges of recommendation systems for software development. 11-15 - Christopher Scaffidi, Christopher Bogart
Characterizing reusability of end-user web macro scripts. 1
Short talks
- Marcel Bruch, Thorsten Schäfer, Mira Mezini:
On evaluating recommender systems for API usages. 16-20 - Prasun Dewan:
Dimensions of tools for detecting software conflicts. 21-25 - Lijie Zou, Michael W. Godfrey:
Understanding interaction differences between newcomer and expert programmers. 26-29 - Irina Ioana Brudaru, Andreas Zeller
What is the long-term impact of changes? 30-32 - Mark Grechanik
Evaluating recommended applications. 33-35 - P. F. Xiang, Annie T. T. Ying, P. Cheng, Ya Bin Dang, Kate Ehrlich, Mary E. Helander, Paul Matchen, A. Empere, Peri L. Tarr, Clay Williams, S. X. Yang:
Ensemble: a recommendation tool for promoting communication in software teams. 2
Posters
- Emerson R. Murphy-Hill, Andrew P. Black
Seven habits of a highly effective smell detector. 36-40 - Yana Momchilova Mileva, Andreas Zeller
Project-specific deletion patterns. 41-42 - Adrian Schröter, Irwin Kwan, Lucas D. Panjer, Daniela E. Damian:
Chat to succeed. 43-44 - J. Andres Diaz-Pace, Len Bass, Felix Bachmann, Philip Bianco:
Towards an agent-based framework for guiding design exploration. 45-49 - Bogdan Dit, Andrian Marcus
Improving the readability of defect reports. 47-49 - Jose Romero-Mariona, Hadar Ziv, Debra J. Richardson:
SRRS: a recommendation system for security requirements. 50-52 - Marcel Bruch, Mira Mezini:
Improving code recommender systems by incorporating domain knowledge and graphical models. 3
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