@inproceedings{Peruma:icsmeTool:IDEAL,
title = {IDEAL: An Open-Source Identifier Name Appraisal Tool},
author = {Anthony Peruma and Venera Arnaoudova and Christian Newman},
year = {2021},
date = {2021-07-17},
booktitle = {Proceedings of the International Conference on Software Maintenance and Evolution (ICSME) - Demonstrations Track},
keywords = {Tool},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{2021-ICSETool-gazel,
title = {gazel: Supporting Source Code Edits in Eye-Tracking Studies},
author = {Sarah Fakhoury and Devjeet Roy and Harry Pines and Tyler Cleveland and Cole S. Peterson and Venera Arnaoudova and Bonita Sharif and Jonathan I. Maletic},
url = {http://veneraarnaoudova.com/wp-content/uploads/2021/02/2020-ICSE-tool-PREPRINT-gazel-Supporting-Source-Code-Edits-inEye-Tracking-Studies.pdf},
year = {2021},
date = {2021-05-01},
booktitle = {Proceedings of the International Conference on Software Engineering (ICSE) - Demonstrations Track},
pages = {69--72},
abstract = {The paper presents a novel solution to capturing eye movements on source code within an IDE in the presence of edits. The solution is presented as an extension of the iTrace [9] community infrastructure and it introduces the iTrace-Atom plugin and gazel—a Python data processing pipeline that allows to track gaze information on changing source code. iTrace-Atom is evaluated via a series of simulations and is over 99% accurate at high eye-tracking speeds of over 1000Hz. Our approach completely revolutionizes the way eye tracking studies can be conducted in realistic settings all with the presence of scrolling, context switching and now editing. This opens the doors to supporting many day-to-day software engineering tasks such as bug fixing, adding new features, and refactoring.
The paper presents a novel solution to capturing eye movements on source code within an IDE in the presence of edits. The solution is presented as an extension of the iTrace [9] community infrastructure and it introduces the iTrace-Atom plugin and gazel—a Python data processing pipeline that allows to track gaze information on changing source code. iTrace-Atom is evaluated via a series of simulations and is over 99% accurate at high eye-tracking speeds of over 1000Hz. Our approach completely revolutionizes the way eye tracking studies can be conducted in realistic settings all with the presence of scrolling, context switching and now editing. This opens the doors to supporting many day-to-day software engineering tasks such as bug fixing, adding new features, and refactoring.
@inproceedings{Roy:icseTool:VITALSE,
title = {VITALSE: Visualizing Eye Tracking and Biometric Data},
author = {Devjeet Roy and Sarah Fakhoury and Venera Arnaoudova},
url = {http://veneraarnaoudova.com/wp-content/uploads/2020/02/2020-ICSE_Tool-PREPRINT-VITALSE-Visualizing-Eye-Tracking-and-Biometric-Data.pdf},
year = {2020},
date = {2020-05-01},
booktitle = {Proceedings of the International Conference on Software Engineering (ICSE) - Demonstrations Track},
pages = {57--60},
keywords = {Biometrics, empirical study, program comprehension, Tool},
pubstate = {published},
tppubtype = {inproceedings}
}
