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
Clustering of model instances by using graph kernels. Make sure you test your models with the most diverse set of examples!
When testing or validating a model we need a diverse set of instances that helps us to analyze the different ways such model can be satisfied. Our work uses classifying terms and constraint strengthening to generate such diverse set.
We present our ecosystem of tools to facilitate the automatic discovery, merging, quality assurance and code-generation of REST APIs, relying on standard specifications like OpenAPI and OData.
We propose to employ graph kernels for clustering software modeling artifacts. Among other benefits, this would improve the efficiency and usability of a variety of software modeling activities, e.g., design space exploration, testing or verification and validation.
Our special issue on Quality in Model-Driven Engineering has now been finalized and published online in the Computer Languages, Systems & Structures journal linked to the Quality Aspects in Model Driven Engineering track at QUATIC 2016
