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vizSlice: An Approach for Understanding Slicing Data via Visualization

Kaczka Jennings, Rachel Ania
http://orcid.org/0000-0001-9695-9395
http://rave.ohiolink.edu/etdc/view?acc_num=miami1493378579021583

Abstract Details

2017, Master of Science, Miami University, Computer Science and Software Engineering.
Several approaches have been suggested for computing program slices based on different perspectives, including forward slicing, backward slicing, static slicing, and dynamic slicing. The applications of slicing are numerous, including testing, effort estimation, and impact analysis. Surprisingly, given the maturity of slicing, few approaches exist for visualizing slices. Here we present our research for visualizing large systems based on program slicing. In particular, we use treemaps to facilitate hierarchical, slicing-based navigation, we use bipartite graphs to facilitate visual impact analysis over a given variable or line of code, parallel coordinates to facilitate visual impact analysis over code blocks or variable groupings, and a text-based code browser to provide detailed context for the relevant visualizations. We believe our tools support various software maintenance tasks, including providing analysts an interactive visualization of the impact of potential changes, thus allowing developers to plan maintenance accordingly. We evaluate the research by assessing usability through a think aloud protocol and a heuristic evaluation. Our results indicate users could effectively complete the evaluation tasks we provided, and the visual idioms utilized in vizSlice were effective at communicating the underlying data to them. However, controls for these visualizations need improvement in both affordance and visibility. Regardless of any difficulties users experienced with vizSlice, users consistently rated the system positively on the measured heuristics. We provide insights on these results, future plans for improving vizSlice, and provide guidance for future research on visualizing program slices.
Gerald Gannod (Advisor)
Hakam Alomari (Committee Member)
Matthew Stephan (Committee Member)
James Kiper (Committee Member)
Computer Science
program visualization; program slicing; visual analytics; slicing visualization; static forward slicing

Recommended Citations

Citations

  • Kaczka Jennings, R. A. (2017). vizSlice: An Approach for Understanding Slicing Data via Visualization [Master's thesis, Miami University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=miami1493378579021583

    APA Style (7th edition)

  • Kaczka Jennings, Rachel. vizSlice: An Approach for Understanding Slicing Data via Visualization. 2017. Miami University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=miami1493378579021583.

    MLA Style (8th edition)

  • Kaczka Jennings, Rachel. "vizSlice: An Approach for Understanding Slicing Data via Visualization." Master's thesis, Miami University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=miami1493378579021583

    Chicago Manual of Style (17th edition)

miami1493378579021583
474
© 2017, all rights reserved.
This open access ETD is published by Miami University and OhioLINK.