Can EEG Be Adopted as a Neuroscience Reference for Assessing Software Programmers’ Cognitive Load?
Júlio Medeiros,
Ricardo Couceiro,
Gonçalo Duarte,
João Durães,
João Castelhano,
Catarina Duarte,
Miguel Castelo-Branco,
Henrique Madeira,
Paulo de Carvalho,
César Teixeira
Affiliations
Júlio Medeiros
Department of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, P-3030-790 Coimbra, Portugal
Ricardo Couceiro
Department of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, P-3030-790 Coimbra, Portugal
Gonçalo Duarte
Department of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, P-3030-790 Coimbra, Portugal
João Durães
Department of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, P-3030-790 Coimbra, Portugal
João Castelhano
ICNAS-Institute of Nuclear Sciences Applied to Health, University of Coimbra, P-3000-548 Coimbra, Portugal
Catarina Duarte
ICNAS-Institute of Nuclear Sciences Applied to Health, University of Coimbra, P-3000-548 Coimbra, Portugal
Miguel Castelo-Branco
ICNAS-Institute of Nuclear Sciences Applied to Health, University of Coimbra, P-3000-548 Coimbra, Portugal
Henrique Madeira
Department of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, P-3030-790 Coimbra, Portugal
Paulo de Carvalho
Department of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, P-3030-790 Coimbra, Portugal
César Teixeira
Department of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, P-3030-790 Coimbra, Portugal
An emergent research area in software engineering and software reliability is the use of wearable biosensors to monitor the cognitive state of software developers during software development tasks. The goal is to gather physiologic manifestations that can be linked to error-prone scenarios related to programmers’ cognitive states. In this paper we investigate whether electroencephalography (EEG) can be applied to accurately identify programmers’ cognitive load associated with the comprehension of code with different complexity levels. Therefore, a controlled experiment involving 26 programmers was carried. We found that features related to Theta, Alpha, and Beta brain waves have the highest discriminative power, allowing the identification of code lines and demanding higher mental effort. The EEG results reveal evidence of mental effort saturation as code complexity increases. Conversely, the classic software complexity metrics do not accurately represent the mental effort involved in code comprehension. Finally, EEG is proposed as a reference, in particular, the combination of EEG with eye tracking information allows for an accurate identification of code lines that correspond to peaks of cognitive load, providing a reference to help in the future evaluation of the space and time accuracy of programmers’ cognitive state monitored using wearable devices compatible with software development activities.
