GUI Test Repair Based on Test-Extension

GUI test repair is important to detect and repair obsolete test events to enhance the reliability of the software. From an interaction design perspective, designers usually design different routes to facilitate users to reach the same functional entry point. Based on this, we propose a novel test repair method to find paths with similar functions based on the feature coverage, to get as close as possible to the test target point during the repairing process, and to improve the effectiveness of the test fixing. A test extension algorithm is proposed to search for alternative event branches with similar features to the test script. Then, the sequence transduction probability is used to calculate the feature coverage of the mapping event paths in the updated version and guide the repair. Experiments conducted on popular applications demonstrate that the method can achieve a success rate of 79.63% in repairing tests, which significantly outperforms current approaches. The test-extension approach displays immense potential for optimizing test repairs.

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Publication Details

Published
2024-10-18
DOI
https://doi.org/10.1145/3691620.3695323
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
0.00

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article

GUI Test Repair Based on Test-Extension

Yonghao Long, Yuanyuan Chen, Xiangping Chen
Industrial Vision Systems and Defect Detection
article

GUI Test Repair Based on Test-Extension

Yonghao Long, Yuanyuan Chen, Xiangping Chen
article en

Abstract

GUI test repair is important to detect and repair obsolete test events to enhance the reliability of the software. From an interaction design perspective, designers usually design different routes to facilitate users to reach the same functional entry point. Based on this, we propose a novel test repair method to find paths with similar functions based on the feature coverage, to get as close as possible to the test target point during the repairing process, and to improve the effectiveness of the test fixing. A test extension algorithm is proposed to search for alternative event branches with similar features to the test script. Then, the sequence transduction probability is used to calculate the feature coverage of the mapping event paths in the updated version and guide the repair. Experiments conducted on popular applications demonstrate that the method can achieve a success rate of 79.63% in repairing tests, which significantly outperforms current approaches. The test-extension approach displays immense potential for optimizing test repairs.

Sun Yat-sen University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 74%
Industrial Vision Systems and Defect Detection
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