A test automation solution on GUI functional test

Zhu, Xiao‐Hua; Zhang, Bo; Li, Juefeng; Qiu, Gao

doi:10.1109/indin.2008.4618325

Cited by 12 publications

(2 citation statements)

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“…al [14] provide a solution for automated GUI functional test in which the authors design a test driver to integrate the tools for test case generation, selection, execution, and reporting. The solution uses the KDF approach and relies on the IBM Rational Functional Tester (RFT) to execute the test scripts, which needs the GUIs to be designed first then captured and recognized by RFT.…”

Section: Related Workmentioning

confidence: 99%

Automated web testing based on textual-visual UI patterns

Zhou

Yin

2014

SIGSOFT Softw. Eng. Notes

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Automated software testing is the only resort for delivering quality software, since there are usually large test suites to be executed, especially for regression testing. Though many automated testing tools and techniques have been developed, they still do not solve all problems like cost and maintenance, and they can even be brittle in some situations, thus confining their adoption. To address these issues, we develop a pattern-based automated testing framework, called UTF (User-oriented Testing Framework), for Web applications. UTF encodes textual-visual information about and relationships between widgets into a domain specific language for test scripts based on the underlying invariant structural patterns in the DOM, which allows test scripts to be easily created and maintained. In addition, UTF provides flexible extension and customization capabilities to make it adaptable for various Web-application scenarios. Our experiences show UTF can greatly reduce the cost of adopting automated testing and facilitate its institutionalization.

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Section: Related Workmentioning

confidence: 99%

Automated web testing based on textual-visual UI patterns

Zhou

Yin

2014

SIGSOFT Softw. Eng. Notes

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“…With the rapid development of Internet applications, especially in mobile devices, the design and testing of GUI around various businesses is becoming increasingly complex. Traditional manual testing can no longer meet the needs of GUI testing [3,4]; hence, automated testing technology is necessary to solve these problems.…”

Section: Introductionmentioning

confidence: 99%

YOLOv5-MGC: GUI Element Identification for Mobile Applications Based on Improved YOLOv5

Cheng

Tan

Zhang

et al. 2022

Mobile Information Systems

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The identification of interface elements is the first step in mobile application automated testing and the key to smooth testing. However, existing object detection algorithms have a low accuracy rate, and some tiny elements are missed in the recognition of graphical user interface (GUI) elements. To address this limitation, this paper proposes the YOLOv5-MGC algorithm, a robot vision-based interface element recognition algorithm for mobile applications. The algorithm improves the network by using K-means++ algorithm for target anchor box generation, applying the attention mechanism, adding a microscale detection layer, and introducing the Ghost bottleneck module. The proposed approach enhances the recognition accuracy of the elements through the target anchor box and attention mechanism. Moreover, it enhances the network’s ability to detect tiny elements, which improves the shortcomings of the current target detection algorithm and is conducive to further promoting mobile application robot testing and enhancing robot testing automation. Experimental results show that the YOLOv5-MGC algorithm is superior to the YOLOv5 for object detection in the recognition of GUI elements, with the mean average precision (mAP_0.5) reaching 89.8% and the recognition precision reaching 80.8%.

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