Qualitative Evaluation of N-Way Model Matching Approaches
- In product line engineering tasks, the need for merging models from different product
variants emerges as the commonly used clone-and-own approach suffers from high
maintenance costs in the long run. By identifying models with a high number of similarities
we can merge them to one highly reusable model. This approach will increase the
maintainability, and further expandability of the model.
Already many works have been published aiming to solve this problem with different
N-way model Matching approaches. However, there is lack of practical evidence that the
published theories work as designed in real world cases.
In this work, we will evaluate relevant published approaches and then attempt to
integrate the most promising one in the product line analysis framework VARIOUS from
Fraunhofer IESE. Next, the implemented approach will be evaluated in comparison to the
existing mechanism for model matching that VARIOUS integrates that is called "System
Aligner". The main aspects of our evaluation are:
• Accuracy - Can it accurately find the most similar models?
• Performance - How fast is it?
• Scalability - How well does it scale in large amount of input models?
• Configurability - Can it be adapted easily for different systems?