Examining Factors Influencing Cognitive Load of Computer Programmers

Abstract

In this study, the factors influencing the cognitive load of computer programmers during the perception of different code tasks were investigated. The eye movement features of computer programmers were used to provide a significant relationship between the perceptual processes of the sample codes and cognitive load. Thanks to the relationship, the influence of various personal characteristics of programmers on cognitive load was examined. Various personal parameters such as programming experience, age, native language, and programming frequency were used in the study. The study was performed on the Eye Movements in Programming (EMIP) dataset containing 216 programmers with different characteristics. Eye movement information recorded during two different code comprehension tasks was decomposed into sub-information, such as pupil movement speed and diameter change. Rapid changes in eye movement signals were adaptively detected using the z-score peak detection algorithm. Regarding the cognitive load calculations, canonical correlation analysis was used to build a statistically significant and efficient mathematical model connecting the extracted eye movement features and the different parameters of the programmers, and the results were statistically significant. As a result of the analysis, the factors affecting the cognitive load of computer programmers for the related database were converted into percentages, and it was seen that linguistic distance is an essential factor in the cognitive load of programmers and the effect of gender on cognitive load is quite limited.