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Feature Modeling vs. Decision Modeling: History, Comparison and Perspectives

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

Modeling variability, i.e., defining the commonalities and variability of reusable artifacts, is a central task of software product line engineering. Numerous variability modeling approaches have been proposed in the last three decades. Most of these approaches are based on feature modeling (FM) or decision modeling (DM), two classes of variability approaches that go back to initial proposals made in the early 1990ies, i.e., FODA for FM and Synthesis for DM. This extended abstract summarizes the history of FM and DM as well as the results of a systematic comparison between FM and DM published earlier. We also outline perspectives, especially regarding potential synergies and key common elements that should be part of a standard variability modeling language.
Original languageEnglish
Title of host publicationFirst International Workshop on Languages for Modelling Variability (MODEVAR 2019), collocated with the 23rd International Systems and Software Product Line Conference (SPLC 2019)
EditorsCarlos Cetina, Oscar Diaz, Laurence Duchien, Marianne Huchard, Rick Rabiser, Camille Salinesi, Christoph Seidl, Xhevahire Ternava, Leopoldo Teixeira, Thomas Thum, Tewfik Ziadi
Place of PublicationParis, France
PublisherACM
Pages134-136
Number of pages3
ISBN (Electronic)9781450366687
DOIs
Publication statusPublished - 09 Sept 2019

Publication series

NameACM International Conference Proceeding Series
VolumeB

Fields of science

  • 102 Computer Sciences
  • 102022 Software development
  • 102025 Distributed systems

JKU Focus areas

  • Digital Transformation

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