OLAP Visual Analytics on Large Software Call Graphs with Hierarchical ChordMap

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The performance of call graph analytics is critical to the development and management of large-scale software systems. Classical call graph visualizers either reuse a plain node-link graph metaphor that does not scale, or adopt the specific aggregation technique like the PivotGraph. In this paper, we first generalize the OLAP analysis framework from multidimensional data to multivariate graphs. Then we introduce Hierarchical ChordMap, a new visualization design that tightly couples with OLAP operations through context-preserving user interactions. Controlled user study demonstrates significant improvements of our design from the basic call graph visualizer. Implications are summarized on when and how the ChordMap design can outperform a stable PivotGraph tool in call graph analysis.

Original languageEnglish
Title of host publicationProceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015
EditorsXindong Wu, Alexander Tuzhilin, Hui Xiong, Jennifer G. Dy, Charu Aggarwal, Zhi-Hua Zhou, Peng Cui
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages675-679
Number of pages5
ISBN (Electronic)9781467384926
DOIs
StatePublished - 29 Jan 2016
Externally publishedYes
Event15th IEEE International Conference on Data Mining Workshop, ICDMW 2015 - Atlantic City, United States
Duration: 14 Nov 201517 Nov 2015

Publication series

NameProceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015

Conference

Conference15th IEEE International Conference on Data Mining Workshop, ICDMW 2015
Country/TerritoryUnited States
CityAtlantic City
Period14/11/1517/11/15

Keywords

  • OLAP
  • Software Analytic
  • Visualization

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