A primary limitation of existing GUI test generators is their inability to produce semantically meaningful test cases, often resulting in tests that are either meaningless or unrepresentative of the application’s intended usage. To address this issue, recent research has focused on the automated adaptation of GUI tests across applications sharing semantic similarities. The core idea is to generate semantically meaningful test cases by adapting human-written test cases for another app with similar functionalities. This approach, often called test reuse, ensures that the adapted tests exercise the app under test in a meaningful way while also allowing for the adaptation of human-written oracles, making test adaptation a potentially powerful alternative to traditional GUI test generators. In this talk, I will present a recent test reuse approach and the results of an empirical study aimed at evaluating the effectiveness of current test reuse techniques. The insights from this talk will hopefully help the research community in developing more effective test reuse approaches and encourage more researchers to work on this promising research topic.