English

eye2vec: Learning Distributed Representations of Eye Movement for Program Comprehension Analysis

Software Engineering 2025-10-16 v2

Abstract

This paper presents eye2vec, an infrastructure for analyzing software developers' eye movements while reading source code. In common eye-tracking studies in program comprehension, researchers must preselect analysis targets such as control flow or syntactic elements, and then develop analysis methods to extract appropriate metrics from the fixation for source code. Here, researchers can define various levels of AOIs like words, lines, or code blocks, and the difference leads to different results. Moreover, the interpretation of fixation for word/line can vary across the purposes of the analyses. Hence, the eye-tracking analysis is a difficult task that depends on the time-consuming manual work of the researchers. eye2vec represents continuous two fixations as transitions between syntactic elements using distributed representations. The distributed representation facilitates the adoption of diverse data analysis methods with rich semantic interpretations.

Keywords

Cite

@article{arxiv.2510.11722,
  title  = {eye2vec: Learning Distributed Representations of Eye Movement for Program Comprehension Analysis},
  author = {Haruhiko Yoshioka and Kazumasa Shimari and Hidetake Uwano and Kenichi Matsumoto},
  journal= {arXiv preprint arXiv:2510.11722},
  year   = {2025}
}

Comments

Accepted for publication in the 2025 ACM Symposium on Eye Tracking Research & Applications (ETRA2025) LBW : 3 pages, 1 figure

R2 v1 2026-07-01T06:34:36.850Z