MLContext: A Context-Modeling Language for Context-Aware Systems

Abstract

Context awareness refers to systems that can both sense and react based on their environment. The complexity of these systems makes necessary to apply software engineering techniques in their development, such as Model-Driven Software development (MDD). One of the main difficulties that developers of context-aware systems must tackle is how to manage the needed context information. In this paper, we present MLContext, a textual Domain Specific Language (DSL) which is specially tailored for modeling context information and automatically generating software artefacts from context models. It has been designed to provide a high-level abstraction, to be an easy to learn, and to promote reuse of context models. We have built a toolkit including an editor and a parser to convert MLContext textual specifications into models. As a proof of concept, we have automatically generated ontologies and Java code for the OCP middleware. MLContext models can be reused in applications with the same context because they do not include details related to the platforms or the implementation. These context models can be specified by non-developers users because MLContext provides high-level abstractions of the domain.