In recent years, the use of biological signals to understand the oper- ations of software engineers has emerged, although with a limited understanding of its successful application. This paper provides primary evidence that biological signals obtained by electroen- cephalography (EEG) may provide valuable information from the perspective of software engineers, who then decode the adequacy, consistency, and efficiency of their work. The experimentation with 20 different professional male software engineers has been completed. Two natural situations have been investigated: pair programming and programming with (without) music. The early findings show the methodology’s effectiveness

Thapaliya A, Amirova R, Busechian S, Ivanov V, Masyagin S, Shakirov R, et al. (2021). Fundamental Contemplation on the Adequacy of the Analysis of Brain Waves: Case of EEG. USA : Association for Computing Machinery, Inc. (ACM) [10.1145/3467707.3467742].

Fundamental Contemplation on the Adequacy of the Analysis of Brain Waves: Case of EEG

Succi G;
2021

Abstract

In recent years, the use of biological signals to understand the oper- ations of software engineers has emerged, although with a limited understanding of its successful application. This paper provides primary evidence that biological signals obtained by electroen- cephalography (EEG) may provide valuable information from the perspective of software engineers, who then decode the adequacy, consistency, and efficiency of their work. The experimentation with 20 different professional male software engineers has been completed. Two natural situations have been investigated: pair programming and programming with (without) music. The early findings show the methodology’s effectiveness
2021
ICCAI '21: 2021 7th International Conference on Computing and Artificial Intelligence
233
237
Thapaliya A, Amirova R, Busechian S, Ivanov V, Masyagin S, Shakirov R, et al. (2021). Fundamental Contemplation on the Adequacy of the Analysis of Brain Waves: Case of EEG. USA : Association for Computing Machinery, Inc. (ACM) [10.1145/3467707.3467742].
Thapaliya A; Amirova R; Busechian S; Ivanov V; Masyagin S; Shakirov R; Succi G; Tarasau H; Tormasov A; Zufarova O
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/892468
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