Toward empirically-based software visualization languages

Underlying any single-user software visualization (SV) system is a visualization language onto which its users must map the computations they would like to visualize with the system. We hypothesize that the usability of such systems turns on their ability to provide an underlying visualization language that accords with the ways in which their users conceptualize the computations to be visualized. To explore the question of how to design visualization languages grounded in human conceptualization, we present an empirical study that made use of a research method called visualization storyboarding to investigate the human conceptualization of the bubblesort algorithm. Using an analytical framework based on entities, attributes, and transformations, we derive a semantic-level visualization language for bubblesort, in terms of which all visualizations observed in our study can be expressed. Our empirically-based visualization language provides a means for predicting the usability of the visualization language defined by Lens (Mukherjea and Stasko, 1994), a prototypical single-user SV system. We draw from a follow-up usability study of Lens to substantiate our predictions.