METHODS AND ARCHITECTURAL APPROACHES TO AUTOMATING THE TESTING OF MOBILE AND WEB APPLICATIONS

Abstract

The research presents a comprehensive analysis of software testing automation, specifically focusing on mobile and web applications. While manual testing remains common, its limitations – such as low repeatability and high labor intensity – often lead to errors and increased development costs. Thus, automated testing is essential for accelerating functional verification and optimizing expenses in highly competitive markets.

The primary aim of this study is to enhance quality assurance (QA) efficiency by developing a scientifically grounded method for the rational selection of an automation architecture. The methodology examines modern QA practices, architectural patterns, and the ISO/IEC 25010:2023 standard. This standard defines product quality through eight core characteristics, forming specific requirements for the test framework architecture to ensure reliable validation.

A comparative analysis of Linear, Modular, Data-Driven (DDF), Keyword-Driven (KDF), and Behavior-Driven (BDD) frameworks was conducted using expert evaluations across implementation speed, support cost, flexibility, skill requirements, and ROI. Acknowledging that no classic pattern is universally applicable, the study introduces an adaptive architecture selection method based on the mathematical formalization of input project parameters. The algorithm correlates framework selection with expected development duration, team expertise, business requirements, and data variability. This allows engineers to make deterministic decisions during planning, mitigating risks.

The developed method was validated by modeling architectural solutions for MVP/Prototypes, FinTech/Banking systems, and E-commerce CMS. Implementing this approach transitions QA from intuitive tool selection to engineering-based design. This prevents the accumulation of technical debt, effectively reducing the Total Cost of Ownership (TCO) of the automation system by 30-40% over the long term. Ultimately, test automation serves as a strategic risk management tool, resolving the trade-off between time-to-market and product quality.