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P2 Practical Escape of Exploration Tarpits for Mini-Game Testing in an Industrial Setting

工业场景下小游戏测试中探索陷阱的实用逃逸方法
ASE 2025 40th IEEE/ACM International Conference on Automated Software Engineering (ASE)2025匹配度 2/10 · 论文聚焦微信小游戏的自动化 UI 测试,通过视觉线索检测并逃逸滑动手势探索陷阱,属于软件测试/调试与修复方向;但未涉及静态分析、LLM/Agent、浮点程序分析或贝叶斯程序分析,与用户研究画像的核心问题基本无关。其工业部署与问题驱动特点与用户的部分偏好一致,但主题匹配度很低。引用 0 inbox
Yuan Cao, Dezhi Ran, Haochuan Lu, Chao Guo, Xuran Hao, Zhuoru Chen, Ting Xiong, Yuetang Deng, Tao Xie
crossref: 2026-09-12

AI 速览

一句话:提出 SlideScout,利用视觉线索检测并逃逸滑动手势探索陷阱,提升微信小游戏自动化 UI 测试效率。

微信小游戏平台拥有数十万款上线小游戏,自动化 UI 测试是保障体验的关键。但滑动手势会引发“探索陷阱”,使测试工具陷入重复无效手势,最多浪费 98% 的测试预算。工业场景下利用视觉线索(如滑动指示器)逃逸陷阱面临两大挑战:仅凭不连续截图推断线索的鲁棒性,以及以低开销支撑数千并发测试的效率。本文报告 SlideScout:并发监控测试进度,在截图时检测滑动指示器并复用预处理结果;用多种启发式重建候选轨迹;执行推断手势直至逃逸,便于集成现有工具。在微信内部部署六个月,发现 25,000 次崩溃与 120,000 个 JavaScript 错误,同期崩溃检出较基线提升 50%,并总结三条经验。

问题
微信小游戏自动化 UI 测试中,滑动手势导致的探索陷阱使测试工具陷入重复无效手势,最多浪费 98% 的测试预算;而利用视觉线索逃逸又受限于不连续截图的鲁棒性与数千并发测试的效率要求。
方法
提出三阶段方法 SlideScout:并发监控测试进度并在收集截图时检测滑动指示器、复用预处理结果;用多种启发式从不连续截图中重建候选滑动轨迹;持续施加推断出的滑动手势直至成功逃逸陷阱。
评估
在微信内部部署六个月,帮助发现 25,000 次崩溃和 120,000 个 JavaScript 错误,同期崩溃检出量比部署前基线多 50%,并总结了三条开发与部署经验。
原文摘要(Abstract)

Attracting over one billion registered users globally, WeChat’s mini-game platform has become one of the largest gaming platforms with hundreds of thousands of published mini-games. To ensure the quality of experiences across a massive number of mini-games, automated UI testing has become essential for WeChat. However, sliding-gesture-induced exploration tarpits, states where a testing tool becomes trapped in repetitive, unsuccessful gesture attempts, cause the testing tool to waste up to 98% of its testing budget due to its inability to execute proper sliding gestures. While mini-games typically contain visual hints (e.g., sliding indicators) guiding the desired sliding gestures, exploiting these hints to escape exploration tarpits faces two major challenges in industrial settings: (1) robustness challenge when exploiting hints from only several discontinuous screenshots, and (2) efficiency challenge to support thousands of concurrent testing services with minimal overhead and costs.To address the preceding challenges, we report our experiences in developing and deploying SlideScout, a three-stage approach for detecting and escaping sliding-gesture-induced exploration tarpits via efficient exploitation of visual hints. First, SlideScout concurrently monitors the testing progress and detects sliding indicators alongside screenshot collection, improving efficiency by reusing preprocessed results in subsequent stages. Second, SlideScout reconstructs potential sliding trajectories using multiple heuristics, addressing robustness challenges when precise trajectories are unavailable due to discontinuous screenshots. Third, SlideScout applies the inferred sliding gestures until it successfully escapes the tarpit, enabling easy integration with existing testing tools. Deployed at WeChat internally for six months, SlideScout has helped reveal 25,000 crashes and 120,000 JavaScript errors, detecting 50% more crashes compared to the pre-deployment baseline within the same time period. We summarize three major lessons learned from developing and deploying SlideScout.

链接与引用

DOI 原文 ·

BibTeX
@inproceedings{paperbot9493,
  title = {Practical Escape of Exploration Tarpits for Mini-Game Testing in an Industrial Setting},
  author = {Yuan Cao and Dezhi Ran and Haochuan Lu and Chao Guo and Xuran Hao and Zhuoru Chen and Ting Xiong and Yuetang Deng and Tao Xie},
  booktitle = {ASE},
  year = {2025},
  doi = {10.1109/ase63991.2025.00258}
}