The explosive growth of mobile applications has transformed user expectations for performance and reliability. This study examines advanced performance testing methodologies and quality assurance frameworks for mobile application development through mixed-methods research, combining systematic literature review with empirical case studies across seven leading organizations. Results demonstrate that AI-enhanced automated testing frameworks achieve 91% defect detection accuracy while reducing testing cycle time by 68%. Cloud-based cross-platform testing strategies show 85% improvement in device coverage compared to traditional approaches. Integrated CI/CD testing pipelines reduce time-to-market by 47% while maintaining 96% quality gate compliance. The findings suggest that hybrid testing architectures combining automated frameworks, real device testing, and AI-driven analytics provide optimal quality assurance for modern mobile applications.
Tariq Abdullah (Thu,) studied this question.
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