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GPCE 2016
Mon 31 October - Tue 1 November 2016 Amsterdam, Netherlands
co-located with SPLASH 2016
Tue 1 Nov 2016 11:00 - 11:30 at Zürich 1 - Feature Models and Product Lines Chair(s): Christoph Seidl

Today’s competitive marketplace requires the industry to understand unique and particular needs of their customers. Product line practices enable companies to create individual products for every customer by providing an interdependent set of features. Users configure personalized products by consecutively selecting desired features based on their individual needs. However, as most features are interdependent, users must understand the impact of their gradual selections in order to make valid and desired decisions. Thus, especially when dealing with large feature models, specialized assistance is needed to guide the users in configuring their product. Recently, recommender systems have proved to be an appropriate mean to assist users in finding information and making decisions. In this paper, we propose an advanced feature recommender system that provides personalized recommendations to users. In detail, we offer four main contributions: (i) We provide a recommender system that suggests relevant features to ease the decision-making process. (ii) Based on this system, we provide visual support to users that guides them through the decision-making process and allows them to focus on valid and relevant parts of the configuration space. (iii) We provide an interactive open-source configurator tool encompassing all those features. (iv) In order to demonstrate the performance of our approach, we compare three different recommender algorithms in two real case studies derived from business experience.

Conference Day
Tue 1 Nov

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

10:30 - 12:10
Feature Models and Product LinesGPCE at Zürich 1
Chair(s): Christoph SeidlTechnische Universität Braunschweig
A Change-Centric Approach to Compile Configurable Systems with #ifdefs
Larissa BrazFederal University of Campina Grande, Rohit GheyiUFCG, Brazil, Melina Mongiovi, Márcio RibeiroFederal University of Alagoas (UFAL), Flavio Medeiros, Leopoldo TeixeiraFederal University of Pernambuco
A Feature-Based Personalized Recommender System for Product-Line Configuration
Juliana Alves PereiraUniversity of Magdeburg, Pawel MatuszykUniversity of Magdeburg, Sebastian KrieterMagdeburg University, Myra SpiliopoulouUniversity of Magdeburg, Gunter SaakeMagdeburg University
Explaining Anomalies in Feature Models
Matthias KowalTU Braunschweig, Germany, Sofia AnanievaFZI Research Center for Information Technology, Thomas ThümTU Braunschweig, Germany