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Algorithm Animation Using Data Flow Tracing

机译:使用数据流跟踪的算法动画

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摘要

Successful algorithm visualization inherently provides a high level of abstraction, supplying an extra information on the semantics that is behind the code. The postulate of designing highly abstract visualizations is stated as being in a deep contradiction with postulate of automation of the designer's work. The goal of the presented work is partial reconciling these two contradicted postulates. Some elements that significantly increase the level of abstraction may be introduced to the visualization in a strictly automatic mode. To obtain this result, an original method of algorithm animation based on data flow tracing is proposed. Its key idea is to acquire information by observing elementary operations of data flow. For dynamic analysis of nonlocal flows Petri net formalism is used. The new method has been successfully applied in an algorithm animation system Daphnis.
机译:成功的算法可视化从本质上提供了高度的抽象,从而提供了有关代码背后语义的额外信息。据说设计高度抽象的可视化的假设与设计师工作自动化的假设存在着深刻的矛盾。提出的工作的目标是部分和解这两个矛盾的假设。可以在严格的自动模式下将一些显着提高抽象级别的元素引入可视化。为了获得此结果,提出了一种基于数据流跟踪的算法动画的原始方法。其关键思想是通过观察数据流的基本操作来获取信息。为了动态分析非本地流,使用了Petri网形式主义。该新方法已成功应用于算法动画系统Daphnis。

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