Toward tractable instantiation of conceptual data models using non-semantics-preserving model transformations

Abstract

As a bridge from informal business requirements to precise specifications, conceptual models serve a critical role in the development of enterprise systems. Instantiating conceptual models with test data can help stakeholders validate the model and provide developers with a test database to validate their code. ORM is a popular conceptual modeling language due in part to its expressive constraint language. Due to that expressiveness, instantiating an arbitrary ORM model is NP-hard. Smaragdakis et al. identified a subset of ORM called ORM− that can be instantiated in polynomial time. However, ORM− excludes several constraints commonly used in commercial models. Recent research has extended ORM− through semantics-preserving transformations. We extend the set of ORM models that can be transformed to ORM− models by using a class of non-semantics-preserving transformations called constraint strengthening. We formalize our approach as a special case of Stevens’ model transformation framework. We discuss an example transformation and its limitations, and we conclude with a proposal for future research.