An eye-tracking methodology for characterizing program comprehension processes
Proceedings of the 2006 symposium on Eye tracking research & applications
The effects of graphical and textual visualisations in multi-representational debugging environments
HCC '03 Proceedings of the 2003 IEEE Symposium on Human Centric Computing Languages and Environments
Shared visual attention in collaborative programming: a descriptive analysis
Proceedings of the 2010 ICSE Workshop on Cooperative and Human Aspects of Software Engineering
On the use of eye tracking in software traceability
Proceedings of the 6th International Workshop on Traceability in Emerging Forms of Software Engineering
Analysis of code reading to gain more insight in program comprehension
Proceedings of the 11th Koli Calling International Conference on Computing Education Research
Visual attention patterns during program debugging with an IDE
Proceedings of the Symposium on Eye Tracking Research and Applications
An eye-tracking study on the role of scan time in finding source code defects
Proceedings of the Symposium on Eye Tracking Research and Applications
The impact of identifier style on effort and comprehension
Empirical Software Engineering
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The challenges in empirical eye-tracking studies of usability or complex problem solving include 1) how to effectively analyze the eye-tracking data, and 2) how to interpret and relate the resulting measures to the user cognitive processing. We conducted a reanalysis of eye-tracking data from a recent study that involved programmers of two experience groups debugging a program with the help of multiple representations. The proportional fixation time on each area of interest (AOI), frequency of visual attention switches between the areas, and the type of switch were investigated during five consequential phases of ten minutes of debugging. We increased the granularity of the focus on the user processing several times, allowing us to construct a better picture of the process. In addition, plotting the areas of interest in time supported a visual analysis and comparison with the quantitative data. We found repetitive patterns of visual attention that were associated with less experience in programming and lower performance. We also discovered that at the beginning of the process programmers made use of both the code and visualization while frequently switching between them. At a later stage of debugging, more experienced programmers began to increasingly integrate also the output of the program and employed a high-frequency of visual attention switching to coordinate the three representations.