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Correlates of Programmer Efficacy and Their Link to Experience: A Combined EEG and Eye-Tracking Study

Norman Peitek; Annabelle Bergum; Maurice Rekrut; Jonas Mucke; Matthias Nadig; Chris Parnin; Janet Siegmund; Sven Apel
In: ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering. International Symposium on the Foundations of Software Engineering (FSE-2022), November 14-18, Singapore, ACM, 2022.


Background: Despite similar education and background, programmers can exhibit vast differences in efficacy. While research has identified some potential factors, such as programming experience and domain knowledge, the effect of these factors on programmers’ efficacy is not well understood. Aims: We aim at unraveling the relationship between efficacy (speed and correctness) and measures of programming experience. We further investigate the correlates of programmer efficacy in terms of reading behavior and cognitive load. Method: For this purpose, we conducted a controlled experiment with 37 participants using electroencephalography (EEG) and eye tracking. We asked participants to comprehend up to 32 Java sourcecode snippets and observed their eye gaze and neural correlates of cognitive load. We analyzed the correlation of participants’ efficacy with popular programming experience measures. Results: We found that programmers with high efficacy read source code more targeted and with lower cognitive load. Commonly used experience levels do not predict programmer efficacy well, but selfestimation and indicators of learning eagerness are fairly accurate. Implications: The identified correlates of programmer efficacy can be used for future research and practice (e.g., hiring). Future research should also consider efficacy as a group sampling method, rather than using simple experience measures.

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