Managing uncertainty in bidirectional model transformations

Abstract

In Model-Driven Engineering bidirectionality in transformations is regarded as a key mechanism. Recent approaches to non-deterministic transformations have been proposed for dealing with non-bijectivity. Among them, the JTL language is based on a relational model transformation engine which restores consistency by returning all admissible models. This can be regarded as an uncertainty reducing process: the unknown uncertainty at design-time is translated into known uncertainty at run-time by generating multiple choices. Unfortunately, little changes in a model usually correspond to a combinatorial explosion of the solution space. In this paper, we propose to represent the multiple solutions in a intensional manner by adopting a model for uncertainty. The technique is applied to JTL demonstrating the advantages of the proposal.