Multi back-ends for a model library abstraction layer

Abstract

Software development is moving in the direction of modeling as do quite a lot of other IT related tasks. This means, models become more and more important either as a means of communication or as parts of realizations. Unfortunately, these models are rarely reused which might be due to poor tool support. A model recommender system is one possible way out, but it bases on high quality data which is most likely stored in a database and needs to blend into an environment. Hence, approaching model recommendations in a model driven way and generating the underlying data store which makes do with an existing infrastructure is desirable. In this paper we describe the underlying model and the obstacles we had to overcome to make this approach work for relational and non relational databases. © 2013 Springer-Verlag Berlin Heidelberg.