Leveraging Generative AI in Telecom E-commerce: A Framework for Enhanced Development and Testing Optimization
DOI:
https://doi.org/10.32628/CSEIT251112231Keywords:
Generative AI, E-commerce Development, Test Automation, Microservices Testing, DevOps IntegrationAbstract
This article investigates the integration of generative AI technologies within telecom e-commerce platform development and testing workflows. By examining real-world implementations across multiple organizations, the research provides insights into how AI-driven approaches enhance code generation, test coverage, and API optimization in microservices architectures. The article explores the implementation of AI tools within existing CI/CD pipelines, focusing on automated test case generation, dynamic data creation, and intelligent debugging processes. Particular attention is given to security considerations and regulatory compliance, addressing the challenges of AI model explainability and training data quality. The article presents architectural frameworks and best practices for leveraging generative AI while maintaining robust security measures and performance standards. Through case studies and empirical analysis, the article demonstrates the impact of AI integration on development efficiency, test automation, and overall platform reliability. The article contributes significant insights for engineering leaders and architects seeking to implement generative AI solutions in enterprise-scale telecom e-commerce environments, while addressing potential limitations and providing strategies for risk mitigation.
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