Programming is a cognitively demanding exercise. In particular, today’s software development requires a collective effort of programmers and the orchestration of a complex programming infrastructure. As disruptive technologies emerge, e.g., AI and quantum computing, the programming practice is undergoing a change, facing an uncertain future that we may not be able to accurately predict but can envision and work toward. With the maturity of eye-tracking and its integration into everyday consumer electronics such as Alienware’s laptops and Apple’s Vision Pro, we expect it will eventually make its way into everyday use just as touchpad, camera, and micro- phone. Therefore, we see an opportunity to design eye-tracking based assistance to support programmers. Given programmers spend a large amount of their time reading and understanding code, which heavily relies on eyes, we deem this to be a promising problem domain where eye-tracking can be of assistance. To explore this inquiry, we undertook two mapping studies to establish the problem and solution constructs. We then surveyed professional developers to understand this representative cohort of our prospective users and gather concrete, situated problems from them. We conducted these studies under the guiding design science model for empirical software engineering which centers on a problem- solution pair. From the first study, we found that eye-tracking so far is used mostly for education-oriented studies in the research community focused on software devel- opment. There is a need to bring it closer to practitioners. From the second study, we identify that the gaze data produced by eye trackers has been explored with a collection of machine learning techniques. However, these models were trained with small samples that might carry bias and insufficiency. Contemporary ma- chine learning techniques may be able to compensate for that. From the survey, we learned that developers have already adopted AI assistance, and they are mostly positive about it despite room for greater accuracy and capability. As eye-tracking is relatively novel to them, most developers are unsure about how it can help them. For future work, we plan to practice designing with programmers to develop and evaluate our proof of concept and explore gaze data with more tailored ma- chine learning techniques, which aims to generate integration into our system.
@inproceedings{kuang2024developers,author={Kuang, Peng and Söderberg, Emma and Höst, Martin},month=apr,booktitle={Programming '24: Companion Proceedings of the 8th International Conference on the Art, Science, and Engineering of Programming},title={{Developers' Perspective on Today's and Tomorrow's Programming Tool Assistance: A Survey}},year={2024},organization={the 10th Edition of the Programming Experience Workshop},doi={10.1145/3660829.3660848},}
@inproceedings{kuang2024designing,title={Designing A Multi-modal IDE with Developers: An Exploratory Study on Next-generation Programming Tool Assistance},author={Kuang, Peng and S{\"o}derberg, Emma and H{\"o}st, Martin},booktitle={35th Annual Workshop of the Psychology of Programming Interest Group, PPIG 2024},pages={20--36},year={2024},organization={Psychology of Programming Interest Group},}
@inproceedings{mccabe2024ironies,title={Ironies of programming automation: Exploring the experience of code synthesis via large language models},author={McCabe, Alan T and Bj{\"o}rkman, Moa and Engstr{\"o}m, Joel and Kuang, Peng and S{\"o}derberg, Emma and Church, Luke},booktitle={Companion Proceedings of the 8th International Conference on the Art, Science, and Engineering of Programming},pages={12--21},year={2024},doi={10.1145/3660829.3660835},}
@inproceedings{kuang2023devtools,author={Kuang, Peng and Söderberg, Emma and Niehorster, Diederick C and Höst, Martin},booktitle={2023 IEEE/ACM 45th International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER)},month=may,title={{Toward Gaze-assisted Developer Tools}},year={2023},doi={10.1109/icse-nier58687.2023.00015},}
@inproceedings{kuang2023gaze,author={Kuang, Peng and Söderberg, Emma and Niehorster, Diederick C and Höst, Martin},month=may,title={{Applying Machine Learning to Gaze Data in Software Development: a Mapping Study}},year={2023},booktitle={ETRA '23: Proceedings of the 2023 Symposium on Eye Tracking Research and Applications},doi={10.1145/3588015.3589190},}
@inproceedings{mccabe2022visual,title={Visual Cues in Compiler Conversations},author={McCabe, Alan T and S{\"o}derberg, Emma and Church, Luke and Kuang, Peng},booktitle={33th Annual Workshop of the Psychology of Programming Interest Group, PPIG 2022},organization={Psychology of Programming Interest Group},pages={25--38},year={2022},}
