Easing the generation of predictive human performance models from legacy systems

Authors:
Amanda Swearngin;Myra Cohen;Bonnie John;Rachel Bellamy
Affiliations:
University of Nebraska-Lincoln, Lincoln, Nebraska, United States;University of Nebraska-Lincoln, Lincoln, Nebraska, United States;IBM T. J. Watson Research Center, Hawthorne, New York, United States;IBM T. J. Watson Research Center, Hawthorne, New York, United States
Venue:
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Year:
2012

Citing 13
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Abstract

With the rise of tools for predictive human performance modeling in HCI comes a need to model legacy applications. Models of legacy systems are used to compare products to competitors, or new proposed design ideas to the existing version of an application. We present CogTool-Helper, an exemplar of a tool that results from joining this HCI need to research in automatic GUI testing from the Software Engineering testing community. CogTool-Helper uses automatic UI-model extraction and test case generation to automatically create CogTool storyboards and models and infer methods to accomplish tasks beyond what the UI designer has specified. A design walkthrough with experienced CogTool users reveal that CogTool-Helper resonates with a "pain point" of real-world modeling and provide suggestions for future work.