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Due to the importance of Android app quality assurance, many automated GUItesting tools have been developed. Although the test algorithms have beenimproved, the impact of GUI rendering has been overlooked. On the one hand,setting a long waiting time to execute events on fully rendered GUIs slows downthe testing process. On the other hand, setting a short waiting time will causethe events to execute on partially rendered GUIs, which negatively affects thetesting effectiveness. An optimal waiting time should strike a balance betweeneffectiveness and efficiency. We propose AdaT, a lightweight image-basedapproach to dynamically adjust the inter-event time based on GUI renderingstate. Given the real-time streaming on the GUI, AdaT presents a deep learningmodel to infer the rendering state, and synchronizes with the testing tool toschedule the next event when the GUI is fully rendered. The evaluationsdemonstrate the accuracy, efficiency, and effectiveness of our approach. Wealso integrate our approach with the existing automated testing tool todemonstrate the usefulness of AdaT in covering more activities and executingmore events on fully rendered GUIs.

Efficiency Matters: Speeding Up Automated Testing with GUI Rendering Inference