AI-Assisted Test Script Generation for GUI Applications

Automated testing is crucial for ensuring the quality and reliability of modern software applications, especially those with complex graphical user interfaces (GUIs). However, traditional approaches to GUI testing, such as record-and-replay and manual script generation, are often labor-intensive and fail to capture the dynamic nature of user interactions. This paper presents a novel AI-assisted framework for automatically generating test scripts for GUI applications. By leveraging advancements in computer vision and reinforcement learning, the framework accurately detects GUI elements, models user interactions, and generates effective test sequences to validate expected application behavior. The system is evaluated on a diverse set of GUI applications, demonstrating superiority over existing testing methods in terms of test coverage, script generation efficiency, and fault detection capabilities. The results highlight the potential of AI-powered techniques to transform GUI testing, enabling more robust and scalable software development processes.

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Publication Details

Published
2025-01-09
DOI
https://doi.org/10.1109/icaect63952.2025.10958949
Citations
1
Primary Topic
Software Testing and Debugging Techniques
Type
article
Field-Weighted Citation Impact
2.31
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article

AI-Assisted Test Script Generation for GUI Applications

Sanjiv Kapoor
1 citations
Software Testing and Debugging Techniques
2.31
article

AI-Assisted Test Script Generation for GUI Applications

Sanjiv Kapoor
article en
1 citations

Abstract

Automated testing is crucial for ensuring the quality and reliability of modern software applications, especially those with complex graphical user interfaces (GUIs). However, traditional approaches to GUI testing, such as record-and-replay and manual script generation, are often labor-intensive and fail to capture the dynamic nature of user interactions. This paper presents a novel AI-assisted framework for automatically generating test scripts for GUI applications. By leveraging advancements in computer vision and reinforcement learning, the framework accurately detects GUI elements, models user interactions, and generates effective test sequences to validate expected application behavior. The system is evaluated on a diverse set of GUI applications, demonstrating superiority over existing testing methods in terms of test coverage, script generation efficiency, and fault detection capabilities. The results highlight the potential of AI-powered techniques to transform GUI testing, enabling more robust and scalable software development processes.

Amazon (United States) (US)
Openalex Percentile: Top 15%
Software Testing and Debugging Techniques
2.31
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AI-Assisted Test Script Generation for GUI Applications — Sanjiv Kapoor · (2025) | TGRS Research Map | TGRS