Inter-model consistency checking using Triple Graph Grammars and linear optimization techniques

Abstract

An important task in Model-Driven Engineering (MDE) is to check consistency between two concurrently developed yet related models. Practical approaches to consistency checking, however, are scarce in MDE. Triple Graph Grammars (TGGs) are a rule-based technique to describe the consistency of two models together with correspondences. While TGGs seem promising for consistency checking with their precise consistency notion and explicit traceability information, the substantial search space involved in determining the “optimal” set of rule applications in a consistency check has arguably prevented mature tool support so far. In this paper, we close this gap by combining TGGs with linear optimization techniques. We formulate decisions between single rule applications of a consistency check as integer inequalities, which serve as input for an optimization problem used to detect maximum consistent portions of two models. To demonstrate our approach, we provide an experimental evaluation of the tool support made feasible by this formalization.