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Collaborative eye tracking based code review through real-time shared gaze visualization

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Abstract

Code review is intended to find bugs in early development phases, improving code quality for later integration and testing. However, due to the lack of experience with algorithm design, or software development, individual novice programmers face challenges while reviewing code. In this paper, we utilize collaborative eye tracking to record the gaze data from multiple reviewers, and share the gaze visualization among them during the code review process. The visualizations, such as borders highlighting current reviewed code lines, transition lines connecting related reviewed code lines, reveal the visual attention about program functions that can facilitate understanding and bug tracing. This can help novice reviewers to make sense to confirm the potential bugs or avoid repeated reviewing of code, and potentially even help to improve reviewing skills. We built a prototype system, and conducted a user study with paired reviewers. The results showed that the shared real-time visualization allowed the reviewers to find bugs more efficiently.

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Acknowledgements

We thank all the volunteers who took part in the user studies, and all the reviewers who wrote and provided helpful comments on previous versions of this paper. We also gratefully acknowledge the grant from National Natural Science Foundation of China (Grant Nos. 61772468, 62172368), National Key Research & Development Program of China (2016YFB1001403) and Fundamental Research Funds for the Provincial Universities of Zhejiang (RF-B2019001).

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Authors and Affiliations

  1. School of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, 310023, China

    Shiwei Cheng, Jialing Wang, Xiaoquan Shen & Yijian Chen

  2. Information School, University of Washington, Seattle, 98195-9440, USA

    Anind Dey

Authors
  1. Shiwei Cheng
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  2. Jialing Wang
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  3. Xiaoquan Shen
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  4. Yijian Chen
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  5. Anind Dey
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Corresponding author

Correspondence to Shiwei Cheng.

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Shiwei Cheng received the PhD degree in computer science and technology from Zhejiang University, China in 2009. Then, he joined the School of Computer Science and Technology at Zhejiang University of Technology, China, where he became a Professor and Vice Director of the Software Engineering Institute. He has published more than 30 papers in international journals and conferences. He served as committee member of SIGCHI China Chapter, China Computer Federation (CCF) HCI Technical Committee. His research interests include human-computer interaction, ubiquitous computing and collaborative computing.

Jialing Wang is a PhD student in School of Computer Science and Technology at Zhejiang University of Technology, China. His research interest is human-computer interaction.

Xiaoquan Shen is a master student in School of Computer Science and Technology at Zhejiang University of Technology, China. His research interests include human-computer interactionand image processing.

Yijian Chen is a master student in School of Computer Science and Technology at Zhejiang University of Technology, China. His research interests include human-computer interaction and image processing.

Anind Dey is a Professor and Dean of the Information School, University of Washington, USA, and Adjunct Professor in the Department of Human-Centered Design and Engineering. He was inducted into the ACM SIGCHI Academy for his significant contributions to the field of human-computer interaction in 2015. His research interests include the intersection of human-computer interaction, machine learning, and ubiquitous computing.

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Cheng, S., Wang, J., Shen, X. et al. Collaborative eye tracking based code review through real-time shared gaze visualization. Front. Comput. Sci. 16, 163704 (2022). https://doi.org/10.1007/s11704-020-0422-1

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  • DOI: https://doi.org/10.1007/s11704-020-0422-1

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