Decoding the Representation of Code in the Brain: An fMRI Study of Code Review and Expertise

Subjective judgments in software engineering tasks are of critical importance but can be difficult to study with conventional means. Medical imaging techniques hold the promise of relating cognition to physical activities and brain structures. In a controlled experiment involving 29 participants, we examine code comprehension, code review and prose review using functional magnetic resonance imaging. We find that the neural representations of programming languages vs. natural languages are distinct. We can classify which task a participant is undertaking based solely on brain activity (balanced accuracy 79%, p <; 0.001). Further, we find that the same set of brain regions distinguish between code and prose (near-perfect correlation, r = 0.99, p <; 0.001). Finally, we find that task distinctions are modulated by expertise, such that greater skill predicts a less differentiated neural representation (r = -0.44, p = 0.016) indicating that more skilled participants treat code and prose more similarly at a neural activation level.