Context: 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. Objective: In this paper, we thus aim to explore the benefit of simulation to investigate the evolution of model-based product lines. Method: 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). Results: 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. Conclusion: Our results demonstrate that simulation contributes to understanding the effects of maintenance and evolution in model-based product lines.
- Industrial automation systems
- Maintenance and evolution
- Model-based development
- Product line engineering