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ITRACE: AN INFRASTRUCTURE TO SUPPORT EYE-TRACKING STUDIES IN INTEGRATED DEVELOPMENT ENVIRONMENTS

Bryant, Corey A
http://rave.ohiolink.edu/etdc/view?acc_num=kent1626792201600719

Abstract Details

2021, MS, Kent State University, College of Arts and Sciences / Department of Computer Science.
Eye tracking technology has become a powerful tool for understanding how people view and understand visual stimuli. These technologies have been used for years to study how developers read source code when accomplishing various software engineering tasks, however the methods used make little distinction between viewing source code as opposed to generic visual stimuli. Current eye tracking approaches rely predominately on Areas of Interest (AOIs) to match a user’s gazes to specific areas of a fixed image. This approach supports the viewing of smaller code snippets where each line or token can be assigned an AOI. However, files must be predetermined and the AOIs must be plotted manually, meaning that using a larger source code project more reminiscent of real-world systems becomes unfeasible. Today’s software developers work with software containing a multitude of source code files that may be scrolled through and switched between at any given time and iTrace is designed to give developers that freedom during eye tracking studies. The thesis presents the development, architecture, and usage of the iTrace project as an eye tracking infrastructure for recording data within commonly used development environments. iTrace ties directly into development environments such as Microsoft Visual Studio and Eclipse with the use of editor plugins to gather information dynamically and directly from the source. This approach permits the user to scroll through and switch between files as needed during the recording session. A robust post-processing toolkit allows iTrace to automatically generate additional syntactic information by matching the line and column a gaze falls on to a token within the source code file that is viewed. This type of contextual information is often lost when using AOIs where a code snippet is typically isolated from the larger body of source code. Additionally, several fixation filters are currently implemented which can be used to group gazes into fixations directly within the iTrace infrastructure. All this information is gathered into an easy-to-use SQLite database. The more realistic setting iTrace supports allows researchers to verify how well previous AOI based results extend to a more realistic development setting and develop new studies that can fully leverage the features of an integrated development environment.
Jonathan Maletic (Advisor)
Jong-Hoon Kim (Committee Member)
Kwangtaek Kim (Committee Member)
53 p.
Computer Science
software comprehension; eye tracking;

Recommended Citations

Citations

  • Bryant, C. A. (2021). ITRACE: AN INFRASTRUCTURE TO SUPPORT EYE-TRACKING STUDIES IN INTEGRATED DEVELOPMENT ENVIRONMENTS [Master's thesis, Kent State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=kent1626792201600719

    APA Style (7th edition)

  • Bryant, Corey. ITRACE: AN INFRASTRUCTURE TO SUPPORT EYE-TRACKING STUDIES IN INTEGRATED DEVELOPMENT ENVIRONMENTS. 2021. Kent State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=kent1626792201600719.

    MLA Style (8th edition)

  • Bryant, Corey. "ITRACE: AN INFRASTRUCTURE TO SUPPORT EYE-TRACKING STUDIES IN INTEGRATED DEVELOPMENT ENVIRONMENTS." Master's thesis, Kent State University, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=kent1626792201600719

    Chicago Manual of Style (17th edition)

kent1626792201600719
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This open access ETD is published by Kent State University and OhioLINK.