一句话：提出 WebEvo，利用历史页面和计算机视觉区分内容变化与语义结构变化，准确检测 Web 应用演化。
网站演化会导致 IR/RPA 等网页数据提取工具失效，因此需要监控网页变化。现有基于 DOM 树的监测工具常将内容变化误报为有害变化，且无法识别 GUI 组件演化（如按钮移动），难以支持定位器修复。WebEvo 利用历史页面识别可安全忽略的内容变化，并引入计算机视觉技术，在元素级别建立新旧页面 GUI 组件的映射，以检测保持语义与外观的重构变化。在 9 个类别共 13 个真实网站上的实验表明，WebEvo 在有效性和效率上均优于现有 DOM 树检测和整页视觉比较方法。
The development of Web technology and the beginning of the Big Data era have led to the development of technologies for extracting data from websites, such as information retrieval (IR) and robotic process automation (RPA) tools. As websites are constantly evolving, to prevent these tools from functioning improperly due to website evolution, it is important to monitor the changes in websites and report them to the developers and testers. Existing monitoring tools mainly use DOM-tree based techniques to detect changes in the new web pages. However, these monitoring tools incorrectly report content-based changes (i.e., web content refreshed every time a web page is retrieved) as the changes that will adversely affect the performance of the IR and RPA tools. This results in false warnings since the IR and RPA tools typically consider these changes as expected and retrieve dynamic data from them. Moreover, these monitoring tools cannot identify GUI widget evolution (e.g., moving a button), and thus cannot help the IR and RPA tools adapt to the evolved widgets (e.g., automatic repair of locators for the evolved widgets). To address the limitations of the existing monitoring tools, we propose an approach, WebEvo, that leverages historic pages to identify the DOM elements whose changes are content-based changes, which can be safely ignored when reporting changes in the new web pages. Furthermore, to identify refactoring changes that preserve semantics and appearances of GUI widgets, WebEvo adapts computer vision (CV) techniques to identify the mappings of the GUI widgets from the old web page to the new web page on an element-by-element basis. Empirical evaluations on 13 real-world websites from 9 popular categories demonstrate the superiority of WebEvo over the existing DOM-tree based detection or whole-page visual comparison in terms of both effectiveness and efficiency.
DOI 原文 ·
@inproceedings{paperbot6643,
title = {WebEvo: taming web application evolution via detecting semantic structure changes},
author = {Fei Shao and Rui Xu and Wasif Haque and Jingwei Xu and Ying Zhang and Wei Yang and Yanfang Ye and Xusheng Xiao},
booktitle = {ISSTA},
year = {2021},
doi = {10.1145/3460319.3464800}
}