World Journal of Engineering Research and Technology

Gift Aruchi Nwatuzie*

ABSTRACT

Digital Twin (DT) technology has transformed industries by enabling real-time simulations and predictive analytics. However, its application in software engineering remains underexplored. Traditional software testing methods often struggle with real-world variability, leading to undetected defects and security vulnerabilities. This paper introduces aDT-driven software testing framework that enhances reliability, security, and performance validation. The proposed model integrates AI-driven predictive analytics and real-time monitoring to create a high-fidelity, adaptive software validation environment. A comparative study against traditional testing methods demonstrates a 95% defect detection accuracy, a 70% reduction in downtime, and a 50% improvement in debugging efficiency. The findings emphasize DT’s potential in software engineering, providing a foundation for resilient, self-adaptive software systems.

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