Adaptive Requirement Engineering through Digital Twin Feedback Loops

Traditional Requirement Engineering (RE) relies on static specifications that often fail to adapt to evolving stakeholder needs, environmental changes, and runtime feedback. This paper proposes a novel Adaptive Requirement Engineering framework driven by Digital Twin Feedback Loops (ADTF-RE) to enable dynamic adaptation of requirements throughout the system lifecycle. The approach integrates Digital Twin (DT) technology with continuous feedback mechanisms to sense requirement deviations, analyze context changes, and update requirement models in real time. Mathematical modeling, experimental simulations, analytical graphs, and comparative results are provided to validate the proposed methodology. Results demonstrate that ADTF-RE significantly reduces adaptation latency and enhances stakeholder satisfaction compared to traditional RE and static digital twin models.