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Towards Context Modeling for Algorithm Animation

Authors: Xiaocong Zhou; Wenjun Li; Han-jun Xian; Taizong Lai; Hui Liang;

Towards Context Modeling for Algorithm Animation

Abstract

Algorithm animation plays an important role in the education of computing and the development of algorithms. But the lack of explicit modeling of visualization specifications makes it difficult to reuse the algorithm implementations and the specifications. A context-aware algorithm animation framework named CA3F is proposed in this paper to solve the problem. In the CA3F framework, the algorithm execution is abstracted as the creation of algorithm contexts, while the algorithm animation is considered as the visualization of algorithms driven by the change of contexts. Algorithm contexts are modeled as visualization specification explicitly and, in consequence, an algorithm implementation becomes independent of the algorithm animation so as to enhance the reusability of the visualization specification. A group of various sort algorithm animations are developed to demonstrate and evaluate the use of CA3F framework.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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