Visually Analyzing Eye Movements on Natural Language Texts and Source Code Snippets

Abstract : In this paper, we analyze eye movement data of 26 participants using a quantitative and qualitative approach to investigate how people read natural language text in comparison to source code. In particular, we use the radial transition graph visualization to explore strategies of participants during these reading tasks and extract common patterns amongst participants. We illustrate via examples how visualization can play a role at uncovering behavior of people while reading natural language text versus source code. Our results show that the linear reading order of natural text is only partially applicable to source code reading. We found patterns representing a linear order and also patterns that represent reading of the source code in execution order. Participants also focus more on those areas that are important to comprehend core functionality and we found that they skip unimportant constructs such as brackets.
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https://hal.inria.fr/hal-02084109
Contributor : Tanja Blascheck <>
Submitted on : Wednesday, April 3, 2019 - 1:07:36 PM
Last modification on : Friday, August 9, 2019 - 10:46:05 AM

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Tanja Blascheck, Bonita Sharif. Visually Analyzing Eye Movements on Natural Language Texts and Source Code Snippets. ETRA 2019 - ACM Symposium on Eye Tracking Research & Applications, Jun 2019, Denver, United States. ⟨10.1145/3314111.3319917⟩. ⟨hal-02084109⟩

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