Tripel Graph Grammars (TGG) 3.0: A Framework for Reliable, Continuous Model Integration

模型驱动工程(MDE)是一种用于管理日益复杂的工程产品的成熟方法。模型有助于捕捉产品开发的本质。随着工程项目变得越来越复杂，开发团队越来越多地在分布式环境中工作，对模型网络上的协作建模过程的支持变得越来越重要。模型网络上的协同建模还不够成熟，不足以自动检测和解决模型变化之间的不一致和冲突。当前的MDE方法要么只允许同步建模活动，要么在模型元素级别提供具有悲观锁定的“团队变量”，或者仅允许并发编辑模型对的有限可能性。双向转换(BX)有望极大地简化模型同步任务的开发。尽管BX方法在模型对上的基本模型同步过程中已经成熟，但它们在实际应用中仍然存在严重的缺陷，因为模型网络往往是并发变化的，模型不一致并不总是能够立即解决的。现有的方法在实践中并不总是具有足够的伸缩性，或者不能保证计算模型同步的正确性和完整性。为了加强在大型项目中建模的MDE愿景，我们的目标是开发一个可靠、持续的模型集成框架，为跨多个应用领域的协作建模过程提供概念和技术基础。该框架将支持对网络中模型的并发更改的持续集成，同时容忍临时的模型不一致。由于三重图文法(TGGs)是一种基于规则的BX方法，已被证明在实践中工作良好，并具有全面的形式基础，因此我们将在TGG的背景下开发该框架。基于我们在第一个筹资阶段为TGGs开发的改进的模型同步方法和工具，我们的框架将支持合作模型集成商网络的发展。每个模型集成器的任务是在一对相连的模型上执行可靠的、连续的模型集成。为了实现这一目标，每个模型集成器使用由知识组件(MAPE-K-Cycle)驱动的监视-分析-计划-执行-周期；这是从Self-X系统中采用的概念。对于大规模模型集成，我们考虑由并发活动的模型集成商组成的网络。我们的框架将在Arcadia上进行评估，这是一种工业中基于模型的工程的最新方法。

Model-Driven Engineering (MDE) is an established approach to manage the increasing complexity of engineering products. Models help to capture the essence of product developments. As engineering projects tend to become more complex and development teams increasingly work in distributed settings, support for collaborative modelling processes on networks of models becomes more and more important. Collaborative modelling on networks of models is not yet mature enough to automatically detect and resolve inconsistencies and conflicts between model changes. Current MDE methods either allow only synchronous modelling activities, provide a "team variant" with pessimistic locking at the model element level, or allow only limited possibilities for concurrent editing of model pairs.Bidirectional transformations (BX) promise to greatly simplify the development of model synchronization tasks. While BX approaches are mature for basic model synchronization processes on model pairs, they still have severe shortcomings in practical use, as model networks are often changed concurrently and model inconsistencies cannot always be resolved immediately. Existing approaches do not always scale sufficiently in practice or do not guarantee the correctness and completeness of computed model synchronizations. To strengthen the MDE vision for modelling in large projects, we aim to develop a framework for reliable, continuous model integration that provides a conceptual and technological basis for collaborative modelling processes across multiple application domains. This framework will support continuous integration of concurrent changes to models in a network while tolerating temporary model inconsistencies. Since Triple Graph Grammars (TGGs), a rule-based BX-approach, have proven to work well in practice and have a comprehensive formal foundation, we will develop the framework in the context of TGGs. Based on improved model synchronization methods and tools for TGGs that we developed in the first funding phase, our framework will support the development of networks of cooperating model integrators. Each model integrator is tasked with performing reliable, continuous model integration on a pair of connected models. To achieve this goal, each model integrator uses a Monitor-Analyze-Plan-Execute-cycle driven by a knowledge component (MAPE-K-cycle); a concept adopted from Self-X systems. For large-scale model integration, we consider networks of concurrently active model integrators. Our framework will be evaluated at Arcadia, a state-of-the-art methodology for model-based engineering in industry.