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 language | English |
|---|---|
| Title of host publication | First International Workshop on Languages for Modelling Variability (MODEVAR 2019), collocated with the 23rd International Systems and Software Product Line Conference (SPLC 2019) |
| Editors | Carlos Cetina, Oscar Diaz, Laurence Duchien, Marianne Huchard, Rick Rabiser, Camille Salinesi, Christoph Seidl, Xhevahire Ternava, Leopoldo Teixeira, Thomas Thum, Tewfik Ziadi |
| Place of Publication | Paris, France |
| Publisher | ACM |
| Pages | 134-136 |
| Number of pages | 3 |
| ISBN (Electronic) | 9781450366687 |
| DOIs | |
| Publication status | Published - 09 Sept 2019 |
Publication series
| Name | ACM International Conference Proceeding Series |
|---|---|
| Volume | B |
Fields of science
- 102 Computer Sciences
- 102022 Software development
- 102025 Distributed systems
JKU Focus areas
- Digital Transformation
Projects
- 1 Finished
-
Christian Doppler Labor für Monitoring and Evolution of Very-Large-Scale Software Systems
Grünbacher, P. (PI)
01.02.2013 → 31.08.2020
Project: Funded research › CDG - Christian Doppler Research Association
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