Study on Language Foundation for Bidirectional Model Transformation

在模型驱动的软件开发中，双向模型转换对于维护两个模型之间的一致性非常有用。然而，缺乏坚实的语言基础和实用的工具支持系统开发良好的和高效的双向模型转换，阻碍了它的广泛应用。我们解决了这个问题，提出了一种新的双向图转换语言UnQL+，这是单向图查询语言UnQL的扩展，并实现了一个集成的框架，称为GRoundTram，这是精心设计和实现的组合开发行为良好，高效的双向模型转换UnQL。GRoundTram配备了一个用户友好的语言，用于编码双向模型转换，一个新颖的工具，用于验证模型和双向模型转换，一个优化机制，以提高效率，和一个强大的调试环境。

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.