A Novel Method for High-Fidelity Web Element Identification

This paper presents a novel method for identifying Web elements from test scripts by calculating a similarity score between user-provided descriptions in the test scripts and the textual content of Web page elements. The algorithm maps elements described in test scripts to their corresponding HTML components by selecting the most appropriate Web element with the calculated score and user actions. Experimental results demonstrate that the proposed method outperforms the state-of-the-art method in identifying Web elements in accuracy (100% vs. 52.83%), the number of test passed (100% vs. 73.08%), and the average execution time (30s vs. 45s). This capability makes the algorithm a valuable tool for developers and testers involved in Web application development and maintenance, which includes automated testing, Web scraping, and dynamic content manipulation.