by Wolfgang Heider, Roman Froschauer, Paul Grünbacher, Rick Rabiser, Deepak Dhungana
Abstract:
Numerous approaches are available for modeling product lines and their variability. However, the long-term impacts of model-based development on maintenance effort and model complexity can hardly be investigated due to a lack of empirical data. Conducting empirical research in product line engineering is difficult as companies are typically reluctant to provide access to data from their product lines. Also, many benefits of product lines can be measured only in longitudinal studies, which are difficult to perform in most environments. In this paper, we thus aim to explore the benefit of simulation to investigate the evolution of model-based product lines. We present a simulation approach for exploring the effects of product line evolution on model complexity and maintenance effort. Our simulation considers characteristics of product lines (e.g., size, dependencies in models) and we experiment with different evolution profiles (e.g., technical refactoring vs. placement of new products). We apply the approach in a simulation experiment that uses data from real-world product lines from the domain of industrial automation systems to demonstrate its feasibility. Our results demonstrate that simulation contributes to understanding the effects of maintenance and evolution in model-based product lines.
Reference:
Simulating evolution in model-based product line engineering (Wolfgang Heider, Roman Froschauer, Paul Grünbacher, Rick Rabiser, Deepak Dhungana), In Information & Software Technology, volume 52, 2010.
Bibtex Entry:
@ARTICLE{Heider2010,
author = {Wolfgang Heider and Roman Froschauer and Paul Grünbacher and Rick
Rabiser and Deepak Dhungana},
title = {Simulating evolution in model-based product line engineering},
journal = {Information \& Software Technology},
year = {2010},
volume = {52},
pages = {758-769},
number = {7},
abstract = {Numerous approaches are available for modeling product lines and their
variability. However, the long-term impacts of model-based development
on maintenance effort and model complexity can hardly be investigated
due to a lack of empirical data. Conducting empirical research in
product line engineering is difficult as companies are typically
reluctant to provide access to data from their product lines. Also,
many benefits of product lines can be measured only in longitudinal
studies, which are difficult to perform in most environments. In
this paper, we thus aim to explore the benefit of simulation to investigate
the evolution of model-based product lines. We present a simulation
approach for exploring the effects of product line evolution on model
complexity and maintenance effort. Our simulation considers characteristics
of product lines (e.g., size, dependencies in models) and we experiment
with different evolution profiles (e.g., technical refactoring vs.
placement of new products). We apply the approach in a simulation
experiment that uses data from real-world product lines from the
domain of industrial automation systems to demonstrate its feasibility.
Our results demonstrate that simulation contributes to understanding
the effects of maintenance and evolution in model-based product lines.},
doi = {10.1016/j.infsof.2010.03.007},
keywords = {CD Lab ASE}
}