Nishant Mishra
Computer Science
Feburary 2023
The graphical user interface (GUI), which enables you to connect to your application with mouse and keyboard motions, is one of the most popular types of user interface. Although there are tools for automating GUI testing, most of them need a working framework or data relevant to a given structure in order to interface with the application being tested. With time, such devices become obsolete due to operating system changes and a wide range of GUI systems. By employing AI approaches to automatically detect his GUI components in screenshots, it offers a solution to enhance ad hoc GUI tests. Current graphical user interaction testing frameworks automate testing of electronic interfaces to make sure there are no actual or visible mistakes. To deal with different testing use-cases, they employ conventional strategies. This analysis of these methods shows that it is unrealistic to anticipate being able to evaluate a few distinct intuitive interface styles in a comprehensive manner. We propose a sophisticated image-based strategy that combines fresh and tried-and-true strategies. They affect the decomposition and validation of connection point screenshots by AI and PC Vision algorithms. According to the results, it is effective to automate the verification of user-friendly interfaces that were previously only partially testable. Automated tests provide good precision by default and nearly no misleading benefits.
101- 118
© Airo Journals 2021
