Exploring eye tracking data on source code via dual space analysis

Li Zhang, Jianxin Sun, Cole Peterson, Bonita Sharif, Hongfeng Yu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Eye tracking is a frequently used technique to collect data capturing users' strategies and behaviors in processing information. Understanding how programmers navigate through a large number of classes and methods to find bugs is important to educators and practitioners in software engineering. However, the eye tracking data collected on realistic codebases is massive compared to traditional eye tracking data on one static page. The same content may appear in different areas on the screen with users scrolling in an Integrated Development Environment (IDE). Hierarchically structured content and fluid method position compose the two major challenges for visualization. We present a dual-space analysis approach to explore eye tracking data by leveraging existing software visualizations and a new graph embedding visualization. We use the graph embedding technique to quantify the distance between two arbitrary methods, which offers a more accurate visualization of distance with respect to the inherent relations, compared with the direct software structure and the call graph. The visualization offers both naturalness and readability showing time-varying eye movement data in both the content space and the embedded space, and provides new discoveries in developers' eye tracking behaviors.

Original languageEnglish (US)
Title of host publicationProceedings - 7th IEEE Working Conference on Software Visualization, VISSOFT 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages67-77
Number of pages11
ISBN (Electronic)9781728149394
DOIs
StatePublished - Sep 2019
Event7th IEEE Working Conference on Software Visualization, VISSOFT 2019 - Cleveland, United States
Duration: Sep 30 2019Oct 1 2019

Publication series

NameProceedings - 7th IEEE Working Conference on Software Visualization, VISSOFT 2019

Conference

Conference7th IEEE Working Conference on Software Visualization, VISSOFT 2019
CountryUnited States
CityCleveland
Period9/30/1910/1/19

Keywords

  • Content space
  • Developer classification
  • Embedded space
  • Eye tracking
  • Visualization

ASJC Scopus subject areas

  • Software
  • Media Technology

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  • Cite this

    Zhang, L., Sun, J., Peterson, C., Sharif, B., & Yu, H. (2019). Exploring eye tracking data on source code via dual space analysis. In Proceedings - 7th IEEE Working Conference on Software Visualization, VISSOFT 2019 (pp. 67-77). [8900970] (Proceedings - 7th IEEE Working Conference on Software Visualization, VISSOFT 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VISSOFT.2019.00016