Kevoree Modeling Framework (KMF): Efficient modeling techniques for runtime use
This addresses the problem of inefficient modeling tools for developers in IoT and runtime domains, but it appears incremental as it builds on existing standards.
The paper tackles the limitations of the Eclipse Modeling Framework (EMF) in domains like IoT and runtime modeling by proposing the Kevoree Modeling Framework (KMF), which is evaluated and compared to EMF based on identified properties.
The creation of Domain Specific Languages(DSL) counts as one of the main goals in the field of Model-Driven Software Engineering (MDSE). The main purpose of these DSLs is to facilitate the manipulation of domain specific concepts, by providing developers with specific tools for their domain of expertise. A natural approach to create DSLs is to reuse existing modeling standards and tools. In this area, the Eclipse Modeling Framework (EMF) has rapidly become the defacto standard in the MDSE for building Domain Specific Languages (DSL) and tools based on generative techniques. However, the use of EMF generated tools in domains like Internet of Things (IoT), Cloud Computing or Models@Runtime reaches several limitations. In this paper, we identify several properties the generated tools must comply with to be usable in other domains than desktop-based software systems. We then challenge EMF on these properties and describe our approach to overcome the limitations. Our approach, implemented in the Kevoree Modeling Framework (KMF), is finally evaluated according to the identified properties and compared to EMF.