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How People Visually Represent Discrete Constraint Problems

机译:人们如何直观地代表离散的约束问题

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Problems such as timetabling or personnel allocation can be modeled and solved using discrete constraint programming languages. However, while existing constraint solving software solves such problems quickly in many cases, these systems involve specialized languages that require significant time and effort to learn and apply. These languages are typically text-based and often difficult to interpret and understand quickly, especially for people without engineering or mathematics backgrounds. Visualization could provide an alternative way to model and understand such problems. Although many visual programming languages exist for procedural languages, visual encoding of problem specifications has not received much attention. Future problem visualization languages could represent problem elements and their constraints unambiguously, but without unnecessary cognitive burdens for those needing to translate their problem's mental representation into diagrams. As a first step towards such languages, we executed a study that catalogs how people represent constraint problems graphically. We studied three groups with different expertise: non-computer scientists, computer scientists and constraint programmers and analyzed their marks on paper (e.g., arrows), gestures (e.g., pointing) and the mappings to problem concepts (e.g., containers, sets). We provide foundations to guide future tool designs allowing people to effectively grasp, model and solve problems through visual representations.
机译:可以使用离散约束规划语言建模和解决时间表或人员分配等问题。然而,虽然现有的约束解决软件在许多情况下很快解决了此类问题,但这些系统涉及需要大量时间和努力学习和应用的专业语言。这些语言通常是基于文本的,通常很难迅速解释和理解,特别是对于没有工程或数学背景的人。可视化可以提供模拟和理解此类问题的替代方法。虽然存在许多用于程序语言的可视化编程语言,但问题规格的视觉编码并未受到很多关注。未来的问题可视化语言可以毫不含糊地代表问题要素及其约束,但对于需要将其问题的心理表达转化为图表的人来说,没有不必要的认知负担。作为对此类语言的第一步,我们执行了一项研究,目录是人们如何以图形方式代表约束问题。我们研究了三个不同专业知识的组:非计算机科学家,计算机科学家和约束程序员,并在纸上分析了它们的标记(例如,箭头),手势(例如,指向)和问题概念的映射(例如,容器,集合)。我们提供了指导未来工具设计的基础,使人们能够通过视觉表示有效地掌握,模型和解决问题。

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