Towards an affordable brain computer interface for the assessment of programmers' mental workload

This paper provides a proof of concept for the use of wearable technology, and specifically wearable Electroencephalography (EEG), in the field of Empirical Software Engineering. Particularly, we investigated the brain activity of Software Engineers (SEngs) while performing two distinct but related mental tasks: understanding and inspecting code for syntax errors. By comparing the emerging EEG patterns of activity and neural synchrony, we identified brain signatures that are specific to code comprehension. Moreover, using the programmer's rating about the difficulty of each code snippet shown, we identified neural correlates of subjective difficulty during code comprehension. Finally, we attempted to build a model of subjective difficulty based on the recorded brainwave patterns. The reported results show promise towards novel alternatives to programmers' training and education. Findings of this kind may eventually lead to various technical and methodological improvements in various aspects of software development like programming languages, building platforms for teams, and team working schemes.