TY - GEN
T1 - A Flexible Approach for Transforming Variability Models
AU - Feichtinger, Kevin
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/9/6
Y1 - 2021/9/6
N2 - In software product lines, engineers use variability models to explicitly represent commonalities and variability. A plethora of variability modeling approaches have been proposed in the last 30 years, and there is no standard variability modeling approach the community agrees on. Well-known approaches such as feature modeling or decision modeling exist in many different variants, most of which have been shown to be useful for at least one specific use case. Due to this variety of approaches researchers and practitioners alike struggle to find, understand, and eventually pick the right approach for a specific context or (set of) system(s). Practitioners in industry often develop custom solutions to manage the variability of various artifacts, like requirements documents or design spreadsheets. In this paper, we report on our ongoing research towards developing a framework for (semi-)automatically transforming variability models. Our approach supports researchers and practitioners experimenting with and comparing different variability modeling approaches and switching from one modeling approach to another. We present the research questions guiding our research and discuss the current status of our work as well as future work.
AB - In software product lines, engineers use variability models to explicitly represent commonalities and variability. A plethora of variability modeling approaches have been proposed in the last 30 years, and there is no standard variability modeling approach the community agrees on. Well-known approaches such as feature modeling or decision modeling exist in many different variants, most of which have been shown to be useful for at least one specific use case. Due to this variety of approaches researchers and practitioners alike struggle to find, understand, and eventually pick the right approach for a specific context or (set of) system(s). Practitioners in industry often develop custom solutions to manage the variability of various artifacts, like requirements documents or design spreadsheets. In this paper, we report on our ongoing research towards developing a framework for (semi-)automatically transforming variability models. Our approach supports researchers and practitioners experimenting with and comparing different variability modeling approaches and switching from one modeling approach to another. We present the research questions guiding our research and discuss the current status of our work as well as future work.
KW - decision models
KW - feature models
KW - orthogonal variability models
KW - software product lines
KW - variability modeling
UR - https://www.scopus.com/pages/publications/85115175098
U2 - 10.1145/3461002.3473069
DO - 10.1145/3461002.3473069
M3 - Conference proceedings
SN - 978-1-4503-8470-4
T3 - ACM International Conference Proceeding Series
SP - 18
EP - 23
BT - Proc. of the 25th International Systems and Software Product Line Conference (SPLC 2021) vol. 2
A2 - Mousavi, Mohammad
A2 - Schobbens, Pierre-Yves
A2 - Araujo, Hugo
A2 - Schaefer, Ina
A2 - ter Beek, Maurice H.
A2 - Devroey, Xavier
A2 - Rojas, Jose Miguel
A2 - Rabiser, Rick
A2 - Varshosaz, Mahsa
A2 - Kishi, Tomoji
A2 - Lee, Jaejoon
PB - ACM
CY - New York, USA
ER -