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Writing bidirectional model transformations as intentional updates
Author(s) -
Tao Zan,
Hugo Pacheco,
Zhenjiang Hu
Publication year - 2014
Publication title -
portuguese national funding agency for science, research and technology (rcaap project by fct)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1145/2591062.2591102
Subject(s) - computer science , model transformation , synchronization (alternating current) , ambiguity , consistency (knowledge bases) , transformation (genetics) , process (computing) , focus (optics) , distributed computing , artificial intelligence , programming language , computer network , channel (broadcasting) , biochemistry , chemistry , physics , optics , gene
Model synchronization plays an important role in model- driven software development. Bidirectional model transformation approaches provide techniques for developers to specify the bidirectional relationship between source and target models, while keeping related models synchronized for free. Since models of interest are usually not in a one-to-one correspondence, this synchronization process is inherently ambiguous. Nevertheless, existing bidirectional model trans- formation tools focus mainly on enforcing consistency and provide developers only limited control over how models are synchronized, solving the latent ambiguity via default strategies whose behavior is unclear to developers. In this paper, we propose a novel approach in which developers write update programs that succinctly describe how a target model can be used to update a source model, such that the bidirectional behavior is fully determined. The new approach mitigates the unpredictability of existing solutions, by enabling a finer and more transparent control of what a bidirectional transformation does, and suggests a research direction for building more robust bidirectional model transformation tools.

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