Study on Language Foundation for Bidirectional Model Transformation

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Bidirectional model transformation is useful for maintaining consistency between two models in model-driven software development. However, the lack of solid language foundation and a practical tool support for systematic development of well-behaved and efficient bidirectional model transformation prevent it from being widely used. We solve this problem by proposing a novel bidirectional graph transformation language UnQL+ which is an extension of unidirectional graph query language unQL, and implementing an integrated framework called GRoundTram, which is carefully designed and implemented for compositional development of well-behaved and efficient bidirectional model transformations in UnQL. GRoundTram is equipped with a user-friendly language for coding bidirectional model transformation, a novel tool for validating both models and bidirectional model transformations, an optimization mechanism for improving efficiency, and a powerful debugging environment.