EMIP Toolkit: A Python Library for Customized Post-processing of the Eye Movements in Programming Dataset

Madi, Naser Al; Guarnera, Drew T.; Sharif, Bonita; Maletic, Jonathan I.

doi:10.1145/3448018.3457425

Cited by 5 publications

(3 citation statements)

References 30 publications

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“…In this study, we have determined the parameters that affect the cognitive load of computer programmers during code comprehension tasks in percentage terms. We have used the EMIP database, a comprehensive database of eye movements and different personnel parameters of 216 participants [ 33 , 34 ].…”

Section: Discussionmentioning

confidence: 99%

“…The related eye tracking device has a sampling rate of 250 Hz and an accuracy value of <0.4°, and thanks to the high sample rate, it is also suitable for saccadic eye movements detection. When creating the EMIP dataset, two multiple-choice code comprehension tasks were presented to programmers [ 34 ]. These tasks are called the Rectangle and Vehicle tasks, respectively.…”

Section: Methodsmentioning

confidence: 99%

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Examining Factors Influencing Cognitive Load of Computer Programmers

Issever,

Catalbas,

Duran

2023

Brain Sciences

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Examining Factors Influencing Cognitive Load of Computer Programmers

Issever,

Catalbas,

Duran

2023

Brain Sciences

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“…The dataset consists of 47 trials of reading Java code from the Eye Movement In Programming dataset (EMIP) (Bednarik et al, 2020). The EMIP dataset was an international and multi-institutional effort that involved eleven research teams across eight countries on four continents (Al Madi, Guarnera, Sharif, & Maletic, 2021). The trials include multi-line Java source code in medium sized font, and the eye tracker used is an SMI Red 250 eye tracker with 250 samples per second.…”

Section: Methodsmentioning

confidence: 99%

Advancing Dynamic-Time Warp Techniques for Correcting Eye Tracking Data in Reading Source Code

Al Madi

2024

JEMR

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Background: Automated eye tracking data correction algorithms such as Dynamic-Time Warp always made a trade-off between the ability to handle regressions (jumps back) and distortions (fixation drift). At the same time, eye movement in code reading is characterized by non-linearity and regressions. Objective: In this paper, we present a family of hybrid algorithms that aim to handles both regressions and distortions with high accuracy. Method: Through simulations with synthetic data we replicate known eye movement phenomena to assess our algorithms against Warp algorithm as a baseline. Furthermore, we utilize three real datasets to evaluate the algorithms in correcting data from reading source code and see if the proposed algorithms generalize to correcting data from reading natural language text. Results: Our results demonstrate that most proposed algorithms match or outperform baseline warp in correcting both synthetic and real data. Also, we show the prevalence of regressions in reading source code. Conclusion: Our results highlight our hybrid algorithms as an improvement to Dynamic-Time Warp in handling regressions with higher accuracy and better runtime.

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BIGaze: An eye-gaze action-guided Bayesian information gain framework for information exploration

Lee,

Kim,

et al. 2023

Advanced Engineering Informatics

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EMIP Toolkit: A Python Library for Customized Post-processing of the Eye Movements in Programming Dataset

Cited by 5 publications

References 30 publications

Examining Factors Influencing Cognitive Load of Computer Programmers

Examining Factors Influencing Cognitive Load of Computer Programmers

Advancing Dynamic-Time Warp Techniques for Correcting Eye Tracking Data in Reading Source Code

BIGaze: An eye-gaze action-guided Bayesian information gain framework for information exploration

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