![]() To alleviate this technological problem, a novel method for eye tracking data collection is presented. Unfortunately, higher data rates are more desirable as they allow for finer granularity and more accurate study analyses. However, it is not always possible to map each of these points to a line and column position in a source code file (in the presence of scrolling and file switching) in real time at data rates over 60 gaze points per second without data loss. High quality eye trackers can record upwards of 120 to 300 gaze points per second. The use of eye trackers is quickly becoming an important means to study software developers and how they comprehend source code and locate bugs. The paper introduces a fundamental technological problem with collecting high-speed eye tracking data while studying software engineering tasks in an integrated development environment. This paper is intended to be a one-stop resource for researchers interested in designing, executing, and reporting eye tracking studies of software engineering tasks. Finally, we offer lessons learned about using eye trackers to study software engineering tasks. We also discuss the pragmatics of eye tracking studies. We compile a list of typical use cases-real and anticipated-of eye trackers, as well as metrics, visualizations, and statistical analyses to analyze and report eye-tracking data. Based on previous surveys of eye tracking for programming and software engineering tasks and our collective, extensive experience with eye trackers, we discuss when and why researchers should use eye trackers as well as how they should use them. ![]() We begin by presenting the foundations of eye tracking to provide context and perspective. While there are many ways to take advantage of eye trackers, advancing their use requires defining standards for experimental design, execution, and reporting. ![]() Eye trackers provide researchers with insights on software engineers’ cognitive processes, data that can augment those acquired through other means, such as on-line surveys and questionnaires. For several years, the software engineering research community used eye trackers to study program comprehension, bug localization, pair programming, and other software engineering tasks. ![]()
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