Applying Natural Language Processing in Automating User Interface Testing

Authors

  • Vinod kumar Karne QA Automation Engineer
  • Parameshwar Reddy Kothamali QA Automation engineer
  • Noone Srinivas Senior Quality Engineer
  • Nagaraj Mandaloju Senior salesforce developer

Keywords:

Natural Language Processing, UI Testing Automation, Test Case Generation, Execution Performance

Abstract

This study investigates the application of Natural Language Processing (NLP) in automating user interface (UI) testing for web and mobile applications. The primary research problem addressed is how NLP can effectively interpret and execute test cases from natural language descriptions, aiming to streamline and enhance the testing process. The study employs a design that includes developing an NLP-based framework, generating test cases from natural language inputs, and evaluating the framework's performance and accuracy. Key findings reveal that the NLP framework successfully converts natural language descriptions into actionable test cases with high accuracy. It also performs efficiently in executing these test cases and demonstrates effective error detection and reporting. These results support the hypothesis that NLP can significantly improve UI testing by making test case creation more intuitive and automation more effective. The study concludes that NLP-driven automation offers a valuable advancement in UI testing methodologies, suggesting further exploration of advanced NLP techniques and broader application scenarios.

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Published

30-09-2019

How to Cite

Vinod kumar Karne, Parameshwar Reddy Kothamali, Noone Srinivas, & Nagaraj Mandaloju. (2019). Applying Natural Language Processing in Automating User Interface Testing. International Journal for Research Publication and Seminar, 10(3), 111–122. Retrieved from https://jrps.shodhsagar.com/index.php/j/article/view/1531

Issue

Vol. 10 No. 3 (2019): july-sept

Section

Articles

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Copyright (c) 2019 International Journal for Research Publication and Seminar

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