An empirical evaluation of machine learning techniques to classify code comprehension based on EEG data
作者：
Highlights：
• We trained machine learning techniques with electroencephalogram data.
• Machine learning techniques classified developers’ code comprehension.
• Machine learning are effective to classify code comprehension using brain waves.
• The effectivity of machine learning techniques was higher than a random classifier.
• Machine learning techniques presented an effectiveness higher than 80%.
摘要
•We trained machine learning techniques with electroencephalogram data.•Machine learning techniques classified developers’ code comprehension.•Machine learning are effective to classify code comprehension using brain waves.•The effectivity of machine learning techniques was higher than a random classifier.•Machine learning techniques presented an effectiveness higher than 80%.
论文关键词：Code comprehension,Electroencephalography,Machine learning
论文评审过程：Received 30 June 2021, Revised 30 March 2022, Accepted 25 April 2022, Available online 6 May 2022, Version of Record 14 May 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.117354
