Mobile testing is the process of evaluating and assessing the mobile applications’ functionality, performance, visuals, usability, and overall quality. During mobile testing, you test the applications across various devices, OS, screen sizes, and network conditions to ensure they work seamlessly and meet user expectations.
Integrating AI into mobile app testing strategies presents a transformative approach to enhance software quality and streamline development processes. A thorough literature review shows that traditional testing methods face challenges such as manual efforts and limited coverage, necessitating innovation. By leveraging AI techniques like machine learning and natural language processing, testers can automate test case generation, analyze requirements efficiently, and simulate real-world user interactions effectively. Case studies exemplify the tangible benefits of AI-driven testing, including accelerated time-to-market, improved test coverage, and reduced costs. A proposed framework outlines the systematic integration of AI into testing workflows, encompassing data collection, model training, test execution, and result analysis. Empirical validation and continuous refinement ensure the practical applicability of AI-based testing strategies, paving the way for future advancements in software testing practices.