PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
February 5, 20260 citationsOpen Access

A Unified Holistic Model of Visual Perception for Code Reviews

View Full Paper
FHFlorian HäuserTETimur EzerLGLisa Grabinger

Key Points

  • The research aims to create a standardized model for analyzing visual perception during code reviews in software engineering.
  • Adaptation of holistic visual perception models from radiology and psychology.
  • Empirical studies conducted on eye movements during C and C++ code reviews.
  • Analysis of fixation rates, durations, and saccades based on expertise.
  • Identified a phase-based process where experts alternate between global scanning and focused viewing.
  • Significant variations in fixation rates and durations highlight the impact of expertise on visual processing.
  • Defined relevant metrics for eye-tracking analysis applicable to various engineering tasks.

Abstract

Despite being a well-structured domain, software engineering lacks standardized definitions, metrics, and theories for analyzing eye movements in domain-specific tasks. This gap can be addressed by adapting models from other fields, such as radiology and psychology. In particular, the holistic models of image perception provide a suitable framework for software engineering applications. This paper introduces a unified model of visual perception focused on eye movements during code reviews. It is based on prior research, findings from other studies, and cross-domain theories. Empirical studies on C and C++ code reviews confirm a phase-based process, where experts switch between global scanning and focal viewing. In addition, significant differences in the fixation rate, fixation duration, number of saccades, and AOI-specific metrics highlight the role of expertise in visual processing. The proposed model offers a structured framework for eye-tracking analysis in software engineering, defining relevant metrics and supporting future refinements across various software engineering tasks.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Häuser et al. (2025) studied this question.

synapsesocial.com/papers/698433baf1d9ada3c1fb10bchttps://doi.org/10.5283/epub.78551
Ask AI
Helpful
Bookmark
Share
View Full Paper