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UIED: a hybrid tool for GUI element detection

Published: 08 November 2020 Publication History

Abstract

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 User Iterface Element Detection (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: <a>http://uied.online</a>
Github Link: <a>https://github.com/MulongXie/UIED</a>

Supplementary Material

Auxiliary Teaser Video (fse20demo-p40-p-teaser.mp4)
Main presentation
Auxiliary Presentation Video (fse20demo-p40-p-video.mp4)
Main presentation

References

[1]
Lingfeng Bao, Jing Li, Zhenchang Xing, Xinyu Wang, and Bo Zhou. 2015. scvRipper: video scraping tool for modeling developers' behavior using interaction data. In 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering, Vol. 2. IEEE, 673-676.
[2]
Carlos Bernal-Cardenas, Nathan Cooper, Kevin Moran, Oscar Chaparro, Andrian Marcus, and Denys Poshyvanyk. 2020. Translating Video Recordings of Mobile App Usages into Replayable Scenarios. In 42nd International Conference on Software Engineering (ICSE '20). ACM, New York, NY.
[3]
Karl Bridge and Michael Satran. 2018. Windows Accessibility API overview. Retrieved March 2, 2020 from https://docs.microsoft.com/en-us/windows/win32/ winauto/windows-automation-api-portal
[4]
J. Canny. 1986. A Computational Approach to Edge Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-8, 6 (Nov 1986 ), 679-698. https://doi.org/10.1109/TPAMI. 1986.4767851
[5]
Chunyang Chen, Sidong Feng, Zhenchang Xing, Linda Liu, Shengdong Zhao, and Jinshui Wang. 2019. Gallery DC : Design Search and Knowledge Discovery through Auto-created GUI Component Gallery. Proceedings of the ACM on Human-Computer Interaction 3, CSCW ( 2019 ), 1-22.
[6]
Jieshan Chen, Mulong Xie, Zhenchang Xing, Chunyang Chen, Xiwei Xu, Liming Zhu, and Guoqiang Li. 2020. Object Detection for Graphical User Interface: Old Fashioned or Deep Learning or a Combination? arXiv: 2008. 05132 [cs.CV]
[7]
Biplab Deka, Zifeng Huang, Chad Franzen, Joshua Hibschman, Daniel Afergan, Yang Li, Jefrey Nichols, and Ranjitha Kumar. 2017. Rico: A mobile app dataset for building data-driven design applications. In Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology. 845-854.
[8]
Google Developers. 2020. Protocol Bufers &nbsp;|&nbsp; Google Developers. https://developers.google.com/protocol-bufers
[9]
Kaiwen Duan, Song Bai, Lingxi Xie, Honggang Qi, Qingming Huang, and Qi Tian. 2019. Centernet: Keypoint triplets for object detection. In Proceedings of the IEEE International Conference on Computer Vision. 6569-6578.
[10]
Google. 2019. UI Automator. Retrieved March 2, 2020 from https://developer. android.com/training/testing/ui-automator
[11]
Google. 2020. Build more accessible apps. Retrieved March 2, 2020 from https: //developer.android.com/guide/topics/ui/accessibility
[12]
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016. Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition. 770-778.
[13]
Feng Lin, Chen Song, Xiaowei Xu, Lora Cavuoto, and Wenyao Xu. 2016. Sensing from the bottom: Smart insole enabled patient handling activity recognition through manifold learning. In 2016 IEEE First International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE). IEEE, 254-263.
[14]
Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie. 2017. Feature pyramid networks for object detection. In Proceedings of the IEEE conference on computer vision and pattern recognition. 2117-2125.
[15]
Microsoft. 2016. Introducing Spy++. Retrieved March 2, 2020 from https://docs.microsoft.com/en-us/visualstudio/debugger/introducing-spyincrement?view= vs-2019
[16]
Kevin Moran, Boyang Li, Carlos Bernal-Cárdenas, Dan Jelf, and Denys Poshyvanyk. 2018. Automated reporting of GUI design violations for mobile apps. In Proceedings of the 40th International Conference on Software Engineering. 165-175.
[17]
Tuan Anh Nguyen and Christoph Csallner. 2015. Reverse engineering mobile application user interfaces with remaui (t). In 2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE). IEEE, 248-259.
[18]
Suporn Pongnumkul, Mira Dontcheva, Wilmot Li, Jue Wang, Lubomir Bourdev, Shai Avidan, and Michael F Cohen. 2011. Pause-and-play: automatically linking screencast video tutorials with applications. In Proceedings of the 24th annual ACM symposium on User interface software and technology. 135-144.
[19]
Dilip K. Prasad, Maylor K.H. Leung, Chai Quek, and Siu-Yeung Cho. 2012. A novel framework for making dominant point detection methods non-parametric. Image and Vision Computing 30, 11 ( 2012 ), 843-859. https://doi.org/10.1016/j. imavis. 2012. 06.010
[20]
Ju Qian, Zhengyu Shang, Shuoyan Yan, Yan Wang, and Lin Chen. 2020. RoScript: A Visual Script Driven Truly Non-Intrusive Robotic Testing System for Touch Screen Applications. In 42nd International Conference on Software Engineering (ICSE '20). ACM, New York, NY.
[21]
Joseph Redmon and Ali Farhadi. 2018. Yolov3: An incremental improvement. arXiv preprint arXiv: 1804. 02767 ( 2018 ).
[22]
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun. 2015. Faster r-cnn: Towards real-time object detection with region proposal networks. In Advances in neural information processing systems. 91-99.
[23]
H. Samet and M. Tamminen. 1988. Eficient component labeling of images of arbitrary dimension represented by linear bintrees. IEEE Transactions on Pattern Analysis and Machine Intelligence 10, 4 ( 1988 ), 579-586. https://doi.org/10.1109/ 34.3918
[24]
Ray Smith. 2007. An overview of the Tesseract OCR engine. In Ninth International Conference on Document Analysis and Recognition (ICDAR 2007 ), Vol. 2. IEEE, 629-633.
[25]
Satoshi Suzuki and KeiichiA be. 1985. Topological structural analysis of digitized binary images by border following. Computer Vision, Graphics, and Image Processing 30, 1 ( 1985 ), 32-46. https://doi.org/10.1016/ 0734-189X ( 85 ) 90016-7
[26]
OpenCV team. 2020. https://opencv.org/
[27]
Pytorch Team. 2020. https://pytorch.org/
[28]
Shane Torbert. 2016. Applied computer science. Springer.
[29]
Thomas D White, Gordon Fraser, and Guy J Brown. 2019. Improving random GUI testing with image-based widget detection. In Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis. 307-317.
[30]
Tom Yeh, Tsung-Hsiang Chang, and Robert C Miller. 2009. Sikuli: using GUI screenshots for search and automation. In Proceedings of the 22nd annual ACM symposium on User interface software and technology. 183-192.
[31]
Chen Yongxin, Zhang Tonghui, and Chen Jie. 2019. UI2code: How to Fine-tune Background and Foreground Analysis. Retrieved Feb 23, 2020 from https://laptrinhx.com/ui2code-how-to-fine-tune-background-andforeground-analysis-2293652041/
[32]
Dehai Zhao, Zhenchang Xing, Chunyang Chen, Xiwei Xu, Liming Zhu, Guoqiang Li, and Jinshui Wang. 2020. Seenomaly: Vision-Based Linting of GUI Animation Efects Against Design-Don't Guidelines. In 42nd International Conference on Software Engineering (ICSE '20). ACM, New York, NY, 12 pages. https://doi.org/ 10.1145/3377811.3380411
[33]
Xinyu Zhou, Cong Yao, He Wen, Yuzhi Wang, Shuchang Zhou, Weiran He, and Jiajun Liang. 2017. EAST: an eficient and accurate scene text detector. In Proceedings of the IEEE conference on Computer Vision and Pattern Recognition. 5551-5560.

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cover image ACM Conferences
ESEC/FSE 2020: Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering
November 2020
1703 pages
ISBN:9781450370431
DOI:10.1145/3368089
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Published: 08 November 2020

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Author Tags

  1. Computer Vision
  2. Deep Learning
  3. Object Detection
  4. User Interface

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Overall Acceptance Rate 112 of 543 submissions, 21%

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  • (2024)Enabling Cost-Effective UI Automation Testing with Retrieval-Based LLMs: A Case Study in WeChatProceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering10.1145/3691620.3695260(1973-1978)Online publication date: 27-Oct-2024
  • (2024)Beyond Manual Modeling: Automating GUI Model Generation Using Design DocumentsProceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering10.1145/3691620.3695032(91-103)Online publication date: 27-Oct-2024
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  • (2024)LlamaTouch: A Faithful and Scalable Testbed for Mobile UI Task AutomationProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676382(1-13)Online publication date: 13-Oct-2024
  • (2024)Graph4GUI: Graph Neural Networks for Representing Graphical User InterfacesProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642822(1-18)Online publication date: 11-May-2024
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  • (2024)MUD: Towards a Large-Scale and Noise-Filtered UI Dataset for Modern Style UI ModelingProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642350(1-14)Online publication date: 11-May-2024
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