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Complexity Plots
Author(s) -
Thiyagalingam Jeyarajan,
Walton Simon,
Duffy Brian,
Trefethen Anne,
Chen Min
Publication year - 2013
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/cgf.12098
Subject(s) - visualization , computer science , computational complexity theory , focus (optics) , visual analytics , worst case complexity , theoretical computer science , software , categorization , multivariate statistics , data mining , information visualization , algorithm , machine learning , artificial intelligence , programming language , optics , physics
In 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 black‐box software through visualization. Through two case studies, we demonstrate the effectiveness of complexity plots in complexity analysis in research, education and application.