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There’s also a replication package with prompts and analysis tools, and a Twitter thread summary from one of the authors.

Abstract:

Researchers and practitioners have been using code complexity metrics for decades to predict how developers comprehend a program. While it is plausible and tempting to use code metrics for this purpose, their validity is debated, since they rely on simple code properties and rarely consider particularities of human cognition.Aims:We investigate whether and how code complexity metrics reflect difficulty of program comprehension.Method:We have conducted a functional magnetic resonance imaging (fMRI) study with 19 participants observing program comprehension of short code snippets at varying complexity levels.We dissected four classes of code complexity metrics and their relationship to neuronal, behavioral, and subjective correlates of program comprehension, overall analyzing more than 41 metrics.Results:While our data corroborate that complexity metrics can—to a limited degree—explain programmers’ cognition in program comprehension, fMRI allowed us to gain insights into why some code properties are difficult to process. In particular, a code’s textual size drives programmers’ attention, and vocabulary size burdens programmers’ working memory.

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    Really interesting! Notably the lack of correlation between cognitive load and McCabe.