A framework for code-level tracing of map-based algorithm visualizations

J. D. Teresco, Michael A. Dagostino, A. Samad, Eric D. Sauer
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Abstract

This paper presents a framework that has been developed to support code-level tracing of the algorithm visualization capabilities of the Map-based Educational Tools for Algorithm Learning (METAL) project. METAL provides graph data based on real-world highway systems and tools to visualize that data and algorithms which operate on it. Data is shown plotted on maps and in text, color-coded to indicate the progress of the algorithm. The new code-level tracing framework allows specific algorithms to be implemented as a series of small actions, most of which correspond to lines of code that can be highlighted as they are executed. This allows a student to see how specific lines of code affect the data structures and variables as the algorithm makes progress toward a solution.
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基于地图的算法可视化的代码级跟踪框架
本文提出了一个框架,该框架用于支持基于地图的算法学习教育工具(METAL)项目的算法可视化功能的代码级跟踪。METAL提供基于真实公路系统的图形数据,以及可视化数据和操作算法的工具。数据绘制在地图上,并以文字形式显示,用颜色编码表示算法的进展。新的代码级跟踪框架允许将特定算法实现为一系列小操作,其中大多数对应于执行时可以突出显示的代码行。这可以让学生看到特定的代码行是如何影响数据结构和变量的,因为算法正在朝着解决方案前进。
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