(Khmelnytskyi National University, 2025-09) Chaikovskyi, M.A.; Malakhov, E.V.
In the evolving landscape of software engineering, quality assurance (QA) has become increasingly challenging due to the complexity of graphical user interfaces (GUIs), the rapid iteration of user-centric applications, and the limitations of manual and code-based testing frameworks. This paper investigates how computer vision (CV) techniques can improve QA processes by introducing visual-level automation and perception-based testing strategies. Drawing from key studies, this work highlights the achievements and future potential of CV-powered approaches in GUI testing, automated validation, and intelligent interaction with software systems.