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P2 An Empirical Analysis of UI-Based Flaky Tests

基于 UI 的 flaky 测试实证分析
ICSE 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE)2021匹配度 1/10 · 该论文研究 UI flaky tests 的实证分析,属于软件测试与调试领域,与用户关注的形式化/静态分析、LLM/Agent 交叉、浮点程序分析及贝叶斯程序分析均无直接关联。其问题、方法和目标都不在用户研究画像的核心范围内。引用 57 inbox
Alan Romano, Zihe Song, Sampath Grandhi, Wei Yang, Weihang Wang
crossref: 2026-09-12dblp: 2026-09-12arxiv: 2026-09-12

AI 速览

一句话:对 Web 与 Android 项目的 235 个 UI flaky 测试样本进行实证研究,归纳根因、触发策略与修复策略。

现有 flaky test 研究多集中于传统单元测试,忽视 UI 测试输入空间更大、运行条件更多样且更复杂、资源开销高,难以通过重复运行来检测的问题。本文分析来自 62 个 Web 和 Android 项目的 235 个 UI flaky 测试样本,识别其常见根本原因、用于显现 flaky 行为的策略以及修复策略。研究结果为 UI 测试 flakiness 的检测与预防技术奠定基础。

问题
现有 flaky 测试研究主要针对传统单元测试,未充分覆盖输入空间更大、运行条件更多样且资源开销更高的 UI 测试。
方法
对来自 62 个 Web 与 Android 项目的 235 个 flaky UI 测试样本进行实证分析,归纳根因、触发与修复策略。
评估
通过跨 Web 与 Android 项目的人工样本分析总结常见模式,为 UI flaky 测试检测与预防提供基础。
原文摘要(Abstract)

Flaky tests have gained attention from the research community in recent years and with good reason. These tests lead to wasted time and resources, and they reduce the reliability of the test suites and build systems they affect. However, most of the existing work on flaky tests focus exclusively on traditional unit tests. This work ignores UI tests that have larger input spaces and more diverse running conditions than traditional unit tests. In addition, UI tests tend to be more complex and resource-heavy, making them unsuited for detection techniques involving rerunning test suites multiple times. In this paper, we perform a study on flaky UI tests. We analyze 235 flaky UI test samples found in 62 projects from both web and Android environments. We identify the common underlying root causes of flakiness in the UI tests, the strategies used to manifest the flaky behavior, and the fixing strategies used to remedy flaky UI tests. The findings made in this work can provide a foundation for the development of detection and prevention techniques for flakiness arising in UI tests.

链接与引用

DOI 原文 · arXiv · PDF(开放获取) · DBLP

BibTeX
@inproceedings{RomanoSGYW21,
  title = {An Empirical Analysis of UI-Based Flaky Tests},
  author = {Alan Romano and Zihe Song and Sampath Grandhi and Wei Yang and Weihang Wang},
  booktitle = {ICSE},
  year = {2021},
  doi = {10.1109/icse43902.2021.00141}
}