Mobile Application Performance Testing: Advanced Methodologies and Quality Assurance Frameworks for Contemporary Mobile Development

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.

Authors

Publication Details

Journal
International Journal of Mobile Applications and Technologies
Published
2025-10-09
DOI
https://doi.org/10.51137/wrp.ijmat.321
Primary Topic
Mobile and Web Applications
Type
article
Field-Weighted Citation Impact
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article

Mobile Application Performance Testing: Advanced Methodologies and Quality Assurance Frameworks for Contemporary Mobile Development

Tariq Abdullah
International Journal of Mobile Applications and Technologies
Mobile and Web Applications
article

Mobile Application Performance Testing: Advanced Methodologies and Quality Assurance Frameworks for Contemporary Mobile Development

Tariq Abdullah
article en

Abstract

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.

International Journal of Mobile Applications and TechnologiesVol. 1(2)
Openalex Percentile: Top 59%
Mobile and Web Applications
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