Model Matching Challenge: Benchmarks for Ecore and BPMN Diagrams
This addresses a specific bottleneck for software engineers using model-driven tools, but it is incremental as it builds on existing comparison methods.
The paper tackles the problem of low-quality results from state-of-the-art model comparison algorithms in Model Driven Engineering, identifying five edit operations that cause these issues and discussing solutions to improve tool quality.
In the last couple of years, Model Driven Engineering (MDE) gained a prominent role in the context of software engineering. In the MDE paradigm, models are considered first level artifacts which are iteratively developed by teams of programmers over a period of time. Because of this, dedicated tools for versioning and management of models are needed. A central functionality within this group of tools is model comparison and differencing. In two disjunct research projects, we identified a group of general matching problems where state-of-the-art comparison algorithms delivered low quality results. In this article, we will present five edit operations which are the cause for these low quality results. The reasons why the algorithms fail, as well as possible solutions, are also discussed. These examples can be used as benchmarks by model developers to assess the quality and applicability of a model comparison tool for a given model type.