The quality of process descriptions in research is essential to reproducibility and theory building.
We suggest that model-based analysis can contribute to the improvement and concise communication of such descriptions. We demonstrate this by applying a model-based framework – PROVE – to restructure and analyze several process descriptions.
A Body of Knowledge is a fundamental part of any professional discipline because it captures the knowledge that is inherent, sometimes tacit, and often explicit in a professional domain. We propose the MBEBoK as a BoK for the modeling discipline
Second edition of our workshop exploring the mutual benefits of combining model-driven engineering and security techniques.
A Machine Learning approach to determine the conformance of unstructured models against a set of potential metamodels
Use natural language to query your models with our chatbot automatically generated from any domain-model. Built on Eclipse with Xatkit
Quality aspects of an API (availability, performance,…) are key aspects to take into account when deciding which API to choose. Our testing framework provides some insights on these non-functional properties as they are typically not disclosed
Sometimes the easiest way to draw a model is to “write” it down. These tools will render nicely looking UML diagrams from a few lines of text.
Query API specifications in natural language. This chatbot will help you understand what you can do with a given OpenAPI-based API. Including some aspects difficult to get at first sight!
Clustering of model instances by using graph kernels. Make sure you test your models with the most diverse set of examples!
The rising popularity of no-code and low-code tools just shows once again the importance of abstraction mechanisms and (implicit/explicit) models