Deep Learning-Based Mobile Application Isomorphic GUI Identification for Automated Robotic Testing
Publication Date
7-1-2020
Document Type
Article
Publication Title
IEEE Software
Volume
37
Issue
4
DOI
10.1109/MS.2020.2987044
First Page
67
Last Page
74
Abstract
Fully black-box robotic testing is needed given the popularity of mobile applications. A critical constraining issue for generating graphical user interface (GUI) models is identifying isomorphic GUIs. We present a deep learningbased end-to-end trainable model to determine the similarity between GUIs and identify isomorphic GUIs.
Keywords
automatic robotic black-box testing, element recognition, feature extraction, Isomorphic GUI identification, relative entropy
Department
Computer Engineering
Recommended Citation
Tao Zhang, Ying Liu, Jerry Gao, Li Peng Gao, and Jing Cheng. "Deep Learning-Based Mobile Application Isomorphic GUI Identification for Automated Robotic Testing" IEEE Software (2020): 67-74. https://doi.org/10.1109/MS.2020.2987044
