This paper demonstrates AI-driven test automation in complex systems, highlighting significant design techniques and challenges.
Test automation in 2025 is no longer confined to running predefined test cases for static validation. It has evolved into a sophisticated engineering discipline that leverages AI-powered tools, continuous integration, dynamic test case generation, and cloud-native architectures. This paper presents a comprehensive framework for modern test automation that integrates advanced test case design techniques such as Decision Tables, Model-Based Testing, and Risk-Based Prioritization. We explore the role of intelligent test oracles, test observability, and self-healing tests in ensuring software reliability. Key challenges such as GUI event handling, asynchronous workflows, and multi-platform validation are analyzed. The proposed framework supports modular automation, seamless CI/CD integration, and AI-driven test optimization. Through architectural modeling and actionable sequences, this study contributes a holistic roadmap to enhance automation effectiveness and reduce test debt in complex enterprise systems.
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Santosh Kumar Dubey (2025) studied this question.
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