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dc.contributor.authorThiyagalingam, Jeyarajanen_US
dc.contributor.authorWalton, Simonen_US
dc.contributor.authorDuffy, Brianen_US
dc.contributor.authorTrefethen, Anneen_US
dc.contributor.authorChen, Minen_US
dc.contributor.editorB. Preim, P. Rheingans, and H. Theiselen_US
dc.date.accessioned2015-02-28T15:30:26Z
dc.date.available2015-02-28T15:30:26Z
dc.date.issued2013en_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttp://dx.doi.org/10.1111/cgf.12098en_US
dc.description.abstractIn this paper, we present a novel visualization technique for assisting the observation and analysis of algorithmic complexity. In comparison with conventional line graphs, this new technique is not sensitive to the units of measurement, allowing multivariate data series of different physical qualities (e.g., time, space and energy) to be juxtaposed together conveniently and consistently. It supports multivariate visualization as well as uncertainty visualization. It enables users to focus on algorithm categorization by complexity classes, while reducing visual impact caused by constants and algorithmic components that are insignificant to complexity analysis. It provides an effective means for observing the algorithmic complexity of programs with a mixture of algorithms and blackbox software through visualization. Through two case studies, we demonstrate the effectiveness of complexity plots in complexity analysis in research, education and application.en_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.titleComplexity Plotsen_US
dc.description.seriesinformationComputer Graphics Forumen_US


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