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Learning User Interface Element Interactions

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conference contribution
posted on 2023-11-29, 18:10 authored by Christian Degott, Nataniel Pereira Borges Jr., Andreas ZellerAndreas Zeller
When generating tests for graphical user interfaces, one central problem is to identify how individual UI elements can be interacted with---clicking, long- or right-clicking, swiping, dragging, typing, or more. We present an approach based on reinforcement learning that automatically learns which interactions can be used for which elements, and uses this information to guide test generation. We model the problem as an instance of the multi-armed bandit problem (MAB) from probability theory and show how its traditional solutions work on test generation, with and without relying on previous knowledge. The resulting guidance yields higher coverage. In our evaluation, our approach shows improvements in statement coverage between 18% (when not using any previous knowledge) and 20% (when reusing previously generated models).

History

Preferred Citation

Christian Degott, Nataniel Jr. and Andreas Zeller. Learning User Interface Element Interactions. In: International Symposium on Software Testing and Analysis (ISSTA). 2019.

Primary Research Area

  • Secure Connected and Mobile Systems

Name of Conference

International Symposium on Software Testing and Analysis (ISSTA)

Legacy Posted Date

2019-05-02

Open Access Type

  • Unknown

BibTeX

@inproceedings{cispa_all_2883, title = "Learning User Interface Element Interactions", author = "Degott, Christian and Jr., Nataniel Pereira Borges and Zeller, Andreas", booktitle="{International Symposium on Software Testing and Analysis (ISSTA)}", year="2019", }

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