Details zur Publikation
@inproceedings {SchmidRabiserGruenbacher11,
editor={Klaus Schmid and Rick Rabiser and Paul Paul Grünbacher},
title={A Comparison of Decision Modeling Approaches in Product Lines},
publisher={ - ACM},
editor={Patrick Heymans and Krzysztof Czarnecki and Ulrich W. Eisenecker},
booktitle={Proceedings of the 5th International Workshop on Variability Modeling of Software-intensive Systems (VaMoS '11)},
year={2011},
pages={119-126},
doi={10.1145/1944892.1944907},
abstract={It has been shown that product line engineering can significantly improve the productivity, quality and time-to-market of software development by leveraging extensive reuse. Variability models are currently the most advanced approach to define, document and manage the commonalities and variabilities of reusable artifacts such as software components, requirements, test cases, etc. These models provide the basis for automating the derivation of new products and are thus the key artifact to leverage the flexibility and adaptability of systems in a product line. Among the existing approaches to variability modeling feature modeling and decision modeling have gained most importance. A significant amount of research exists on comparing and analyzing different feature modeling approaches. However, despite their significant role in product line research and practical applications, only little effort has been devoted to compare and analyze decision modeling approaches. In order to address this shortcoming and to provide a basis for more structured research on decision modeling in the future, we present a comparative analysis of representative approaches. We identify their major modeling concepts and present an analysis of their commonalities and variabilities.}
}