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<p>One-dimensional statistical methods of scaling have been employed to present a distinct subjective criterion that is related to a measurable aspect of a software component. However, different aspects being measured and different software components being analyzed usually have some characteristics in common. Selected techniques for graphical representation permit a brief but nevertheless thorough view of complex relations among complicated sets of data. Several methods of visualizing and analyzing multidimensional data sets are presented and discussed. The underlying goals of such techniques are to find unknown structures and dependencies among measures, to represent different data sets in order to improve communication and comparability of distinct analyses, and to decrease visual complexity. For improved understandability of the statistical and related graphical concepts, a small set of design aspects from a real-world example is introduced. The techniques illustrated are applied to the same set of data and compared.</p>
correspondence visualisation; software measures; statistical methods; scaling; distinct subjective criterion; graphical representation; multidimensional data sets; dependencies; visual complexity; data visualisation; software metrics; statistical analysis

C. Ebert, "Correspondence Visualization Techniques for Analyzing and Evaluating Software Measures," in IEEE Transactions on Software Engineering, vol. 18, no. , pp. 1029-1034, 1992.
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