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AUITestAgent: Automatic Requirements Oriented GUI Function Testing

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arxiv 2407.09018 v1 pith:4TAENE74 submitted 2024-07-12 cs.SE

classification cs.SE
keywords auitestagentrequirementstesttestingappsinteractionmobileverification
verification ladder T0 review T1 audit T2 compute T3 formal
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The Graphical User Interface (GUI) is how users interact with mobile apps. To ensure it functions properly, testing engineers have to make sure it functions as intended, based on test requirements that are typically written in natural language. While widely adopted manual testing and script-based methods are effective, they demand substantial effort due to the vast number of GUI pages and rapid iterations in modern mobile apps. This paper introduces AUITestAgent, the first automatic, natural language-driven GUI testing tool for mobile apps, capable of fully automating the entire process of GUI interaction and function verification. Since test requirements typically contain interaction commands and verification oracles. AUITestAgent can extract GUI interactions from test requirements via dynamically organized agents. Then, AUITestAgent employs a multi-dimensional data extraction strategy to retrieve data relevant to the test requirements from the interaction trace and perform verification. Experiments on customized benchmarks demonstrate that AUITestAgent outperforms existing tools in the quality of generated GUI interactions and achieved the accuracy of verifications of 94%. Moreover, field deployment in Meituan has shown AUITestAgent's practical usability, with it detecting 4 new functional bugs during 10 regression tests in two months.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. GUIPilot: A Consistency-based Mobile GUI Testing Approach for Detecting Application-specific Bugs

    cs.SE 2025-06 conditional novelty 6.0 of 10

    GUIPilot compares mobile app screens and workflows against design mock-ups, using widget sequence alignment and a vision-language model to detect layout and transition inconsistencies.

  2. TransBench: Breaking Barriers for Transferable Graphical User Interface Agents in Dynamic Digital Environments

    cs.HC 2025-05 conditional novelty 6.0 of 10

    TransBench is a new benchmark of 1,459 screenshots and 22,000 grounding instructions for measuring how well GUI agents transfer across app versions, platforms, and applications.

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