Гібридні методи для вибору тестових селекторів у динамічних веб-додатках

Abstract

The use of hybrid methods for selecting test selectors in dynamic web applications is investigated. It describes the combination of graph neural networks (GNN) with classical selector selection methods, which improves the accuracy and reliability of automated testing. The article also covers the use of statistical metrics to assess the performance of selectors and practical cases of hybrid methods applied in real-world projects. The authors emphasize the importance of integrating innovative technologies to optimize testing and ensure high-quality web applications.