Emily, Thompson and Rajesh, Gupta and Lucas, Fernandes (2023) Enterprise-Scale AI-Augmented Data Engineering: Accelerating the Software Development Lifecycle with GitHub Copilot, Automated Testing Pipelines, and Intelligent Code Review Systems. Innovative: International Multi-disciplinaryJournal of Applied Technology, 1 (1). pp. 112-128. ISSN 2995-486X

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Abstract

The rapid expansion of enterprise-scale software systems has intensified the demand for more efficient, reliable, and intelligent approaches to data engineering and application development. Traditional development lifecycles often suffer from latency, human error, and limited scalability, particularly when integrating complex data pipelines and compliance-driven workflows. This article explores how AI-augmented engineering practices are reshaping the modern software development lifecycle (SDLC), with a focus on three transformative enablers: GitHub Copilot for intelligent code generation, automated testing pipelines for continuous quality assurance, and AI-driven code review systems for enhanced governance and security.

Item Type:	Article
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Postgraduate > Master's of Islamic Education
Depositing User:	Journal Editor
Date Deposited:	18 Sep 2025 08:39
Last Modified:	18 Sep 2025 08:39
URI:	http://eprints.umsida.ac.id/id/eprint/16360

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