When engineering complex systems, models are typically used to represent various systems aspects. These models are often heterogeneous in terms of modeling languages, provenance, number or scale. As a result, the information actually relevant to engineers is usually split into different kinds of interrelated models. To be useful in practice, these models need to be properly integrated to provide global views over the system. This has to be made possible even when those models are serialized or stored in different formats adapted to their respective nature and scalability needs. Model view approaches have been proposed to tackle this issue. They provide unification mechanisms to combine and query various different models in a transparent way. These views usually target specific engineering tasks such as system design, monitoring and evolution. In an industrial context, there can be many large-scale use cases where model views can be beneficial, in order to trace runtime and design-time data, for example. However, existing model view solutions are generally designed to work on top of one single modeling technology (even though model import/export capabilities are sometimes provided). Moreover, they mostly rely on in-memory constructs and low-level modeling APIs that have not been designed to scale in the context of large models stored in different kinds of data sources. This paper presents a general solution to efficiently support scalable model views over heterogeneous modeling resources possibly handled via different modeling technologies. To this intent, it describes our integration approach between a model view framework and various modeling technologies providing access to multiple types of modeling resources (e.g., in XML/XMI, CSV, databases). It also presents how queries on such model views can be executed efficiently by benefiting from the optimization of the different model technologies and underlying persistence backends. Our solution has been evaluated on a practical large-scale use case provided by the industry-driven European MegaM@Rt2 project that aims at implementing a runtime \(\leftrightarrow \) design time feedback loop. The corresponding EMF-based tooling support, modeling artifacts and reproducible benchmarks are all available online.

中文翻译：

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异构建模技术和资源的可扩展模型视图

在设计复杂系统时，通常使用模型来表示各个系统方面。这些模型在建模语言，出处，数量或规模方面通常是异类的。结果，实际上与工程师相关的信息通常被分为不同类型的相互关联的模型。为了在实践中有用，这些模型需要适当地集成以提供系统的全局视图。即使将那些模型序列化或以适合其各自性质和可伸缩性需求的不同格式存储时，也必须使其成为可能。已经提出了模型视图方法来解决这个问题。它们提供了统一的机制，以透明的方式组合和查询各种不同的模型。这些视图通常针对特定的工程任务，例如系统设计，监视和演进。在工业环境中，可能会有许多大型用例，其中的模型视图可能是有益的，例如，以跟踪运行时和设计时数据。但是，现有的模型视图解决方案通常被设计为在一种单独的建模技术之上运行（即使有时会提供模型导入/导出功能）。此外，它们主要依赖于内存中的构造和低级建模API，这些API尚未设计成在存储在不同类型数据源中的大型模型的上下文中可扩展。本文提出了一种通用解决方案，可以有效地支持可能通过不同建模技术处理的异构建模资源上的可伸缩模型视图。为此，它描述了我们在模型视图框架和各种建模技术之间的集成方法，该技术可访问多种类型的建模资源（例如，在XML / XMI，CSV，数据库中）。它还介绍了如何通过受益于不同模型技术和基础持久性后端的优化来有效地执行对此类模型视图的查询。我们的解决方案已在由行业驱动的欧洲MegaM @ Rt2项目提供的实用大规模用例上进行了评估，该项目旨在实现运行时 \（\ leftrightarrow \） 设计时间反馈循环。相应的基于EMF的工具支持，建模工件和可重现的基准均可在线获得。