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Utilizing Machine Learning for the Identification of Visually Similar Web Elements

研究成果: Conference contribution

摘要

A significant proportion of web elements might manifest identical behaviors and functionalities, further complicating the test case creation process. We have noted that elements demonstrating congruent behavior and functionality frequently exhibit visual resemblances within the web page interface. In this paper, we propose a machine learning-based method to identify visually similar web elements. These identified elements can be brought to the attention of the tester. If the tester determines that these elements exhibit similar behavior, they can be visually marked on the web page, facilitating focused test case creation. A case study demonstrates its potential to make accurate judgments on several complex webpages.

原文English
主出版物標題Proceedings - 2023 IEEE International Conference on e-Business Engineering, ICEBE 2023
編輯Omar Khadeer Hussain, Shang-Pin Ma, Xin Lu, Kuo-Ming Chao
發行者Institute of Electrical and Electronics Engineers Inc.
頁面181-186
頁數6
ISBN(電子)9798350325553
DOIs
出版狀態Published - 2023
事件19th IEEE International Conference on e-Business Engineering, ICEBE 2023 - Sydney, Australia
持續時間: 2023 11月 42023 11月 6

出版系列

名字Proceedings - 2023 IEEE International Conference on e-Business Engineering, ICEBE 2023

Conference

Conference19th IEEE International Conference on e-Business Engineering, ICEBE 2023
國家/地區Australia
城市Sydney
期間23-11-0423-11-06

All Science Journal Classification (ASJC) codes

  • 商業、管理和會計(雜項)
  • 人工智慧
  • 電腦網路與通信
  • 資訊系統
  • 資訊系統與管理
  • 安全、風險、可靠性和品質

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