Kusumoto Laboratory: H. Kirinuki, S. Matsumoto, Y. Higo, and S. Kusumoto, Web Element Identification by Combining NLP and Heuristic Search for Web Testing, March 2022.
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H. Kirinuki, S. Matsumoto, Y. Higo, and S. Kusumoto, "Web Element Identification by Combining NLP and Heuristic Search for Web Testing," In 29th edition of the IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), pp. 1044-1054, March 2022.
ID 747
分類 国際会議
タグ testing nlp script
表題 (title) Web Element Identification by Combining NLP and Heuristic Search for Web Testing
表題 (英文) Web Element Identification by Combining NLP and Heuristic Search for Web Testing
著者名 (author) Hiroyuki Kirinuki,Shinsuke Matsumoto,Yoshiki Higo,Shinji Kusumoto
英文著者名 (author) Hiroyuki Kirinuki,Shinsuke Matsumoto,Yoshiki Higo,Shinji Kusumoto
編者名 (editor)
編者名 (英文)
キー (key) Hiroyuki Kirinuki,Shinsuke Matsumoto,Yoshiki Higo,Shinji Kusumoto
書籍・会議録表題 (booktitle) 29th edition of the IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)
書籍・会議録表題(英文)
巻数 (volume)
号数 (number)
ページ範囲 (pages) 1044-1054
組織名 (organization) IEEE
出版元 (publisher)
出版元 (英文)
出版社住所 (address)
刊行月 (month) 3
出版年 (year) 2022
採択率 (acceptance)
URL
付加情報 (note)
注釈 (annote)
内容梗概 (abstract) End-to-end test automation is critical in modern web application development. However, test automation techniques used in industry face challenges in implementing and maintaining test scripts. It is difficult to determine and maintain the locators needed by test scripts to identify web elements on web pages. The reason is that locators depend on the metadata of web elements and the structure of each web page. One effective way to solve such a problem of locators is to allow test cases written in natural language to be executed without test scripts. In this study, we propose a technique to identify web elements that should be operated on a web page by interpreting natural-languagelike test cases. The test cases are written in a domain-specific language that independents on the metadata of web elements and the structural information of web pages. We leverage natural language processing techniques to understand the semantics of web elements. We also create heuristic search algorithms to explore web pages and find promising test procedures. To evaluate the proposed technique, we applied it to test cases for two open-source web applications. The experimental results show that our technique was able to successfully identify about 94% of web elements to be operated in the test cases. Our approach also succeeded in identifying all the web elements that were operated in 68% of the test cases.
論文電子ファイル report.pdf (application/pdf) [一般閲覧可]
BiBTeXエントリ
@inproceedings{id747,
         title = {Web Element Identification by Combining {NLP} and Heuristic Search for Web Testing},
        author = {Hiroyuki Kirinuki and Shinsuke Matsumoto and Yoshiki Higo and Shinji Kusumoto},
     booktitle = {29th edition of the IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)},
         pages = {1044-1054},
    organization = {IEEE},
         month = {3},
          year = {2022},
}
  

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