Rick Rabiser,
"Feature Modeling vs. Decision Modeling: History, Comparison and Perspectives"
: First International Workshop on Languages for Modelling Variability (MODEVAR 2019), collocated with the 23rd International Systems and Software Product Line Conference (SPLC 2019), ACM, Paris, France, Seite(n) 134-136, 9-2019
Original Titel:
Feature Modeling vs. Decision Modeling: History, Comparison and Perspectives
Sprache des Titels:
Englisch
Original Buchtitel:
First International Workshop on Languages for Modelling Variability (MODEVAR 2019), collocated with the 23rd International Systems and Software Product Line Conference (SPLC 2019)
Original Kurzfassung:
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.
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