![](bgb.png)
The use case’s master model and master trans-
formation introduce the benefit of being able to pre-
dict the productivity of yet-to-be-development sys-
tem variants. The use case shows that the benefits
of model-based way of working are not limited to
this. Beside the prediction benefit, our use case re-
veals two additional benefits of the master model and
master transformation: (1) they capture knowledge
in experts’ heads and (2) they provide an additional
means to validate systems.
ACKNOWLEDGEMENTS
The research is carried out as part of the Bright pro-
gram under the responsibility of TNO-ESI with ITEC
as the carrying industrial partner. The Bright research
is supported by the Netherlands Organisation for Ap-
plied Scientific Research TNO.
REFERENCES
Czarnecki, K. and Eisenecker, U. W. (2000). Genera-
tive Programming: Methods, Tools, and Applications.
Addison-Wesley, Reading, MA, USA.
Feng, Y., Dreef, K., Jones, J. A., and van Deursen, A.
(2018). Hierarchical abstraction of execution traces
for program comprehension. In 26th Conference on
Program Comprehension (ICPC ’18), pages 86–96,
Gothenburg, Sweden.
Gad, R. (2017). Improving packet capture trace import in
Trace Compass with a data transformation DSL. In
2017 IEEE 41st Annual Computer Software and Ap-
plications Conference (COMPSAC 2017), volume 2,
pages 7–12, Turin, Italy.
Gr
¨
onniger, H., Krahn, H., Pinkernell, C., and Rumpe, B.
(2008). Modeling variants of automotive systems us-
ing views. In Klein, T. and Rumpe, B., editors, Mod-
ellbasierte Entwicklung von eingebetteten Fahrzeug-
funktionen, number 2008-01 in Informatik-Berichte,
pages 76–89. Technische Universit
¨
at Braunschweig,
Braunschweig, Germany.
Hendriks, M., Verriet, J., Basten, T., Theelen, B., Brass
´
e,
M., and Somers, L. (2017). Analyzing execution
traces: Critical-path analysis and distance analysis.
International Journal on Software Tools for Technol-
ogy Transfer, 19(4):487–510.
Hoffman, C. M. and Joan-Arinyo, R. (1998). CAD and
the product master model. Computer-Aided Design,
30(11):905–918.
Kang, K. C., Cohen, S. G., Hess, J. A., Novak, W. E., and
Peterson, A. S. (1990). Feature-oriented domain anal-
ysis (FODA) feasibility study. Technical report, Soft-
ware Engineering Institute, Carnegie-Mellon Univer-
sity, Pittsburgh, PA, USA.
Meixner, K., Rabiser, R., and Biffl, S. (2019). Towards
modeling variability of products, processes and re-
sources in cyber-physical production systems engi-
neering. In 23rd International Systems and Soft-
ware Product Line Conference (SPLC ’19), volume B,
pages 49–56, Paris, France.
Parappurath, V. V., Voeten, J. P. M., and Kotterink, K. C.
(2013). Calibration error bound estimation in perfor-
mance modeling. In 2013 Euromicro Conference on
Digital System Design, pages 97–102, Los Alamitos,
CA, USA.
Reiss, S. P. (2005). Dynamic detection and visualization of
software phases. In Third International Workshop on
Dynamic Analysis (WODA ’05), pages 1–6, St. Louis,
MI, USA.
Sandberg, M., Tyapin, I., Kokkolaras, M., Isakasson,
O., Aidanp
¨
a
¨
a, J.-O., and Larsson, T. (2011). A
knowledge-based master-model approach with appli-
cation to rotating machinery design. Concurrent En-
gineering, 19(4):295–305.
Tawhid, R. and Petriu, D. (2008). Integrating performance
analysis in the model driven development of software
product lines. In Czarnecki, K., Ober, I., Bruel, J.-
M., Uhl, A., and V
¨
olter, M., editors, MODELS 2008:
Model Driven Engineering Languages and Systems,
pages 490–504. Springer, Berlin, Heidelberg.
van der Linden, F. J., Schmid, K., and Rommes, E. (2007).
Software Product Lines in Action: The Best Indus-
trial Practice in Product Line Engineering. Springer-
Verlag, Berlin, Heidelberg.
van der Sanden, B., Blankenstein, Y., Schiffelers, R., and
Voeten, J. (2021). LSAT: Specification and analysis
of product logistics in flexible manufacturing systems.
In 2021 IEEE 17th International Conference on Au-
tomation Science and Engineering (CASE), pages 1–
8, Lyon, France.
Verriet, J., Dankers, R., and Somers, L. (2018). Per-
formance prediction for families of data-intensive
software applications. In Companion of the 2018
ACM/SPEC International Conference on Perfor-
mance Engineering (ICPE ’18), pages 189–194,
Berlin, Germany.
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