Modeling is requiring increasingly larger efforts while becoming indispensable given the complexity of the problems we are solving. Modelers face high cognitive load to understand a multitude of complex abstractions and their relationships. There is an urgent need to better support tool builders to ultimately provide modelers with intelligent modeling assistance that learns from previous modeling experiences, automatically derives modeling knowledge, and provides context-aware assistance. However, current intelligent modeling assistants (IMAs) lack adaptability and flexibility for tool builders, and do not facilitate understanding the differences and commonalities of IMAs for modelers. Such a patchwork of limited IMAs is a lost opportunity to provide modelers with better support for the creative and rigorous aspects of software engineering. In this expert voice, we present a conceptual reference framework (RF-IMA) and its properties to identify the foundations for intelligent modeling assistance. For tool builders, RF-IMA aims to help build IMAs more systematically. For modelers, RF-IMA aims to facilitate comprehension, comparison, and integration of IMAs, and ultimately to provide more intelligent support. We envision a momentum in the modeling community that leads to the implementation of RF-IMA and consequently future IMAs. We identify open challenges that need to be addressed to realize the opportunities provided by intelligent modeling assistance.

中文翻译：

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智能建模协助的机会

考虑到我们要解决的问题的复杂性，建模需要越来越多的工作，而变得必不可少。建模人员面临很高的认知负担，无法理解众多复杂的抽象及其关系。迫切需要更好地支持工具构建者，以便最终为建模者提供从先前的建模经验中学习，自动获取建模知识并提供上下文感知帮助的智能建模帮助。但是，当前的智能建模助手（IMA）缺乏工具创建者的适应性和灵活性，并且无法帮助理解建模人员的IMA的区别和共性。如此有限的IMA拼凑而成，是一个失去的机会，无法为建模人员提供对软件工程创新和严谨方面的更好支持。以这种专家的声音，我们提出了一个概念性参考框架（RF-IMA）及其属性，以确定智能建模辅助的基础。对于工具制造商而言，RF-IMA旨在帮助更系统地构建IMA。对于建模者而言，RF-IMA旨在促进对IMA的理解，比较和集成，并最终提供更智能的支持。我们设想在建模社区中将有一个动力，该动力将导致RF-IMA的实施，并因此导致未来IMA的实施。我们确定了实现智能建模协助所提供的机会所需要解决的开放挑战。RF-IMA旨在促进对IMA的理解，比较和集成，并最终提供更智能的支持。我们设想建模社区中将有一个动力，从而导致RF-IMA的实施以及因此而来的未来IMA的实施。我们确定了实现智能建模协助所提供的机会所需要解决的开放挑战。RF-IMA旨在促进对IMA的理解，比较和集成，并最终提供更智能的支持。我们设想在建模社区中将有一个动力，该动力将导致RF-IMA的实施，并因此导致未来IMA的实施。我们确定了实现智能建模协助所提供的机会所需要解决的开放挑战。