Graphical User Interface (GUI) elements detection is critical for many GUI automation and GUI testing tasks.
Acquiring the accurate positions and classes of GUI elements is also the very first step to conduct GUI reverse engineering or perform GUI testing.
In this paper, we implement a \textbf{U}ser \textbf{I}terface \textbf{E}lement \textbf{D}etection (UIED), a toolkit designed to provide user with a simple and easy-to-use platform to achieve accurate GUI element detection.
UIED integrates multiple detection methods including old-fashioned computer vision (CV) approaches and deep learning models to handle diverse and complicated GUI images.
Besides, it equips with a novel customized GUI element detection methods to produce state-of-the-art detection results.
Our tool enables the user to change and edit the detection result in an interactive dashboard.
Finally, it exports the detected UI elements in the GUI image to design files that can be further edited in popular UI design tools such as Sketch and Photoshop.
UIED is evaluated to be capable of accurate detection and useful for downstream works.
Tool URL: \url{http://uied.online}
Github Link: \url{https://github.com/MulongXie/UIED}
Thu 12 NovDisplayed time zone: (UTC) Coordinated Universal Time change
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01:00 2mLong-paper | FrUITeR: A Framework for Evaluating UI Test Reuse Research Papers Yixue Zhao University of Massachusetts at Amherst, USA, Justin Chen Columbia University, USA, Adriana Sejfia University of Southern California, USA, Marcelo Schmitt Laser University of Southern California, USA, Jie M. Zhang University College London, UK, Federica Sarro University College London, UK, Mark Harman University College London, UK, Nenad Medvidović University of Southern California, USA DOI Pre-print Media Attached | ||
01:03 1mTalk | ModCon: A Model-Based Testing Platform for Smart Contracts Tool Demos Ye Liu Nanyang Technological University, Singapore, Yi Li Nanyang Technological University, Shang-Wei LIN Nanyang Technological University, Singapore, Qiang Yan WeBank, n.n. DOI Pre-print Media Attached | ||
01:05 1mTalk | Object Detection for Graphical User Interface: Old Fashioned or Deep Learning or a Combination? Research Papers Jieshan Chen Australian National University, Australia, Mulong Xie Australian National University, Australia, Zhenchang Xing Australian National University, Australia, Chunyang Chen Monash University, Australia, Xiwei (Sherry) Xu Data61 at CSIRO, Australia, Liming Zhu Data61 at CSIRO, Australia / UNSW, Australia, Guoqiang Li Shanghai Jiao Tong University, China DOI | ||
01:07 1mTalk | UIED: A Hybrid Tool for GUI Element Detection Tool Demos Mulong Xie Australian National University, Australia, Sidong Feng Australian National University, Australia, Zhenchang Xing Australian National University, Australia, Jieshan Chen Australian National University, Australia, Chunyang Chen Monash University, Australia DOI | ||
01:09 1mTalk | WebRR: Self-Replay Enhanced Robust Record/Replay for Web Application Testing Industry Papers Zhenyue Long China Southern Power Grid, China, Guoquan Wu Institute of Software at Chinese Academy of Sciences, China, Xiaojiang Chen China Southern Power Grid, China, Wei Chen Institute of Software at Chinese Academy of Sciences, China, Jun Wei State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences & University of Chinese Academy of Sciences DOI | ||
01:11 19mTalk | Conversations on Testing 1 Paper Presentations Guoquan Wu Institute of Software at Chinese Academy of Sciences, China, Jieshan Chen Australian National University, Australia, Sidong Feng Australian National University, Australia, Ye Liu Nanyang Technological University, Singapore, Yixue Zhao University of Massachusetts at Amherst, USA, Mulong Xie Australian National University, Australia, M: Corina S. Păsăreanu Carnegie Mellon University Silicon Valley, NASA Ames Research Center | ||