Identifying and Overcoming Obstacles to Effective Software Modeling

软件建模被认为是一种最佳实践，可以快速开发满足用户需求的可靠和安全的软件系统，并提供有效的用户体验。在它们的好处中，模型增加了抽象性，减少了传统代码的开发量，并允许通过多个视图进行验证。然而，从开发人员的角度来看，建模工具和语言仍然存在挑战。许多建模者，特别是学生和其他初学者，会犯系统性错误。大多数工具都过于复杂，无法提供帮助人们避免错误和指导他们更好的建模实践所需的反馈。在这项研究中，我们将继续努力改进建模工具。在过去的15年里，我们开发了Umple，它允许文本和图表建模，具有复杂的关注点分离机制，并支持以多种语言嵌入和生成代码。它试图弥合编程和建模之间的差距，因为它既可以像编程语言一样用于构建完整的系统，也可以作为建模语言（具有模型的文本和图形视图）。Umple被设计成通用的，可以用于在许多领域中对实时系统和信息系统进行建模。它使用起来很简单，但分析模型，提醒开发人员数百种潜在的建模错误，并生成真实的最终系统，包括它自己。有很多文献的挑战，在建模工具的采用和在模型本身的问题，由用户开发。在拟议的研究中，我们计划加深对包括Umple、Papyrus和Astah在内的多种工具的建模弱点的科学理解。我们将研究几种类型的模型中的弱点，在几个不同尺度的几个领域。我们工作的核心是确保建模人员拥有良好的建模体验（MX），并能够将建模作为其整体开发过程的一部分。我们一直致力于将MX挑战归类为工具实用性、可用性、平台因素、情感因素和市场因素。作为这项工作的一部分，我们的目标是进行各种类型的实证研究，以加深对建模挑战的科学理解。这些包括认知步行，构建案例研究系统，观察工作中的真实的用户，以及在Umple上应用设计科学来探索建模工具功能和MX问题。我们的最终目标是改进我们现有的建模实例语料库，制作建模工具弱点目录，开发导致缺乏建模的因素的改进理论，建立一套全面的建模工具设计指南，并应用上述所有内容来改进Umple。Umple的改进工作将使我们能够试验和验证我们工作的其他方面。

Software modeling is considered a best practice to enable rapid development of reliable and secure software systems that meet user requirements and and provide effective user experience. Among their benefits, models increase abstraction, reduce the amount of traditional code developed, and allow verification through multiple views. However from the developer's perspective, tools and languages for modelling continue to have challenges. Many modelers, especially students and other beginners, make systematic errors. Most tools are overly complex and fail to provide the feedback needed to help people avoid errors and to guide them towards better modeling practices. In this research we will continue our work towards improving modeling tools. Over the last 15 years we have developed Umple, which allows textual and diagrammatic modeling, has sophisticated separation of concerns mechanisms, and enables both embedding and generating code in several languages. It attempts to bridge the gap between programming and modeling, since it can be used both like a programming language to construct complete systems, and as a modeling language (with textual and graphical views of models). Umple is designed to be general purpose and can be used to model real-time systems and information systems in many domains. It is deliberately simple to use but analyses models, alerting developers to hundreds of types of potential modeling errors, and generates real final systems, including itself. There has been much literature about challenges in modelling tool adoption and in problems found in models themselves as developed by users. In the proposed research we plan to deepen the scientific understanding of modeling weaknesses in multiple tools including Umple, Papyrus and Astah. We will investigate weaknesses in several types of models, in several domains at several different scales. Central to our work is to ensure that modellers have a good modelling experience (MX) and can perform modelling as a fluid part of their overall development process. We have have been working to catalog MX challenges related to tool utility, usability, platform factors, emotional factors and market factors. As part of this work we aim to conduct various types of empirical studies to deepen the scientific understanding of modelling challenges. These include cognitive walkthroughs, building case study systems, observing real users at work, and applying design science on Umple to explore modelling tool features and MX issues. Our final objectives are to improve our existing corpora of modelling examples, to produce a catalog of modelling tool weaknesses, to develop an improved theory of factors that result in lack of uptake of modelling, to build a comprehensive set of modelling tool design guidelines and to apply all the above to improve Umple. The Umple improvement work will allow us to experiment with and validate the other aspects of our work.