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Can EEG Be Adopted as a Neuroscience Reference for Assessing Software Programmers’ Cognitive Load?

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 t...

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Autores principales: Medeiros, Júlio, Couceiro, Ricardo, Duarte, Gonçalo, Durães, João, Castelhano, João, Duarte, Catarina, Castelo-Branco, Miguel, Madeira, Henrique, de Carvalho, Paulo, Teixeira, César
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8037053/
https://www.ncbi.nlm.nih.gov/pubmed/33801660
http://dx.doi.org/10.3390/s21072338
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author Medeiros, Júlio
Couceiro, Ricardo
Duarte, Gonçalo
Durães, João
Castelhano, João
Duarte, Catarina
Castelo-Branco, Miguel
Madeira, Henrique
de Carvalho, Paulo
Teixeira, César
author_facet Medeiros, Júlio
Couceiro, Ricardo
Duarte, Gonçalo
Durães, João
Castelhano, João
Duarte, Catarina
Castelo-Branco, Miguel
Madeira, Henrique
de Carvalho, Paulo
Teixeira, César
author_sort Medeiros, Júlio
collection PubMed
description 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.
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spelling pubmed-80370532021-04-12 Can EEG Be Adopted as a Neuroscience Reference for Assessing Software Programmers’ Cognitive Load? Medeiros, Júlio Couceiro, Ricardo Duarte, Gonçalo Durães, João Castelhano, João Duarte, Catarina Castelo-Branco, Miguel Madeira, Henrique de Carvalho, Paulo Teixeira, César Sensors (Basel) Article 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. MDPI 2021-03-27 /pmc/articles/PMC8037053/ /pubmed/33801660 http://dx.doi.org/10.3390/s21072338 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Article
Medeiros, Júlio
Couceiro, Ricardo
Duarte, Gonçalo
Durães, João
Castelhano, João
Duarte, Catarina
Castelo-Branco, Miguel
Madeira, Henrique
de Carvalho, Paulo
Teixeira, César
Can EEG Be Adopted as a Neuroscience Reference for Assessing Software Programmers’ Cognitive Load?
title Can EEG Be Adopted as a Neuroscience Reference for Assessing Software Programmers’ Cognitive Load?
title_full Can EEG Be Adopted as a Neuroscience Reference for Assessing Software Programmers’ Cognitive Load?
title_fullStr Can EEG Be Adopted as a Neuroscience Reference for Assessing Software Programmers’ Cognitive Load?
title_full_unstemmed Can EEG Be Adopted as a Neuroscience Reference for Assessing Software Programmers’ Cognitive Load?
title_short Can EEG Be Adopted as a Neuroscience Reference for Assessing Software Programmers’ Cognitive Load?
title_sort can eeg be adopted as a neuroscience reference for assessing software programmers’ cognitive load?
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8037053/
https://www.ncbi.nlm.nih.gov/pubmed/33801660
http://dx.doi.org/10.3390/s21072338
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