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Generating Strictly Controlled Stimuli for Figure Recognition Experiments
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A novel code generator for graphical user interfaces.

Bo Cai1,2, Jian Luo3,4, Zhen Feng3,4

  • 1School of Cyber Science and Engineering, Wuhan University, Wuhan, 430072, China. caib@whu.edu.cn.

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|November 21, 2023
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Summary
This summary is machine-generated.

This study introduces GUICG, an automated tool that converts graphical user interface (GUI) images into source code. GUICG enhances GUI element detection accuracy, significantly aiding front-end development and GUI automation.

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Area of Science:

  • Computer Science
  • Human-Computer Interaction
  • Software Engineering

Background:

  • Graphical User Interfaces (GUIs) are fundamental to modern human-computer interaction.
  • Automating GUI design to source code conversion streamlines front-end development.
  • Accurate GUI element detection is critical for GUI automation and testing but remains a challenge.

Purpose of the Study:

  • To develop an automated system for converting GUI design images into functional source code.
  • To improve the accuracy and localization of GUI element detection in images.
  • To reduce the manual coding effort for front-end developers.

Main Methods:

  • Proposed GUICG, an automatic GUI code generator.
  • Combined deep neural networks with image processing techniques for GUI element detection.
  • Investigated and fused various deep learning and image processing methods for optimal component detection.

Main Results:

  • Achieved state-of-the-art performance in GUI component detection.
  • GUICG demonstrated superior accuracy and F1 scores compared to existing methods.
  • Generated human-readable source code with a logical structure.

Conclusions:

  • GUICG effectively automates GUI code generation by enhancing element detection.
  • The proposed method offers significant improvements over current state-of-the-art techniques.
  • Further ablation studies confirmed the efficacy of GUICG's components.