Unexpected but informative: What fixation-related potentials tell us about the processing of ambiguous program code

• URL: http://arxiv.org/abs/2412.10099v1
• Date: Fri, 13 Dec 2024 12:38:10 GMT
• Title: Unexpected but informative: What fixation-related potentials tell us about the processing of ambiguous program code
• Authors: Annabelle Bergum, Anna-Maria Maurer, Norman Peitek, Regine Bader, Axel Mecklinger, Vera Demberg, Janet Siegmund, Sven Apel,
• Abstract summary: We analyze the online processing of program code patterns that are ambiguous to programmers, but not the computer. Relative to unambiguous counterparts in program code, atoms of confusion elicit a late frontal positivity with a duration of about 400 to 700 ms. We take these data to suggest that the brain engages similar neurocognitive mechanisms in response to unexpected and informative inputs in program code and in natural language.
• Score: 15.510640091254887
• License:
• Abstract: As software pervades more and more areas of our professional and personal lives, there is an ever-increasing need to maintain software, and for programmers to be able to efficiently write and understand program code. In the first study of its kind, we analyze fixation-related potentials (FRPs) to explore the online processing of program code patterns that are ambiguous to programmers, but not the computer (so-called atoms of confusion), and their underlying neurocognitive mechanisms in an ecologically valid setting. Relative to unambiguous counterparts in program code, atoms of confusion elicit a late frontal positivity with a duration of about 400 to 700 ms after first looking at the atom of confusion. As the frontal positivity shows high resemblance with an event-related potential (ERP) component found during natural language processing that is elicited by unexpected but plausible words in sentence context, we take these data to suggest that the brain engages similar neurocognitive mechanisms in response to unexpected and informative inputs in program code and in natural language. In both domains, these inputs lead to an update of a comprehender's situation model that is essential for information extraction from a quickly unfolding input.

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