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dc.contributor.authorStasko, John T.
dc.contributor.authorMuthukumarasamy, Jeyakumar
dc.date.accessioned2004-11-02T16:01:02Z
dc.date.available2004-11-02T16:01:02Z
dc.date.issued1995
dc.identifier.urihttp://hdl.handle.net/1853/3547
dc.description.abstractUnderstanding and interpreting a large data source is an important but challenging operation in many technical disciplines. Computer visualization has become a valuable tool to help capture and portray characteristics of large data sets. In software visualization, illustrating the operation of very large programs or programs working on very large data sets has remained one of the key open problems. Here, we introduce an approach that uses semantic zooming to depict large program executions. Our method utilizes abstract, clustered graphics to portray program operations on the entire data set. Then, by interacting with the presentation, a viewer can zoom in to examine details and individual values. At this "magnified" level, the presentation adjusts to reflect displays common in existing algorithm animation and program visualization systems.en
dc.format.extent154167 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherGeorgia Institute of Technologyen
dc.relation.ispartofseriesGVU Technical Report;GIT-GVU-95-02
dc.subjectSoftware visualizationen
dc.subjectProgram visualizationen
dc.subjectSemantic zoomingen
dc.subjectAlgorithm animationen
dc.titleVisualizing Program Executions on Large Data Sets Using Semantic Zoomingen
dc.typeTechnical Reporten


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