<![CDATA[Regression testing addresses a costly failure mode in enterprise change management, in which a change introduced for one purpose disrupts unrelated functionality. In large-scale SAP environments, regression-scope reference data may already exist as an organizational artifact, yet conventional change preparation does not necessarily consult it systematically, creating regression blindness and exposing production systems to avoidable defects. This study presents Rule R8, an enforced regression cross-check framework embedded within a rules-governed Retrieval-Augmented Generation architecture. The framework integrates regression-scope determination into the same processing pipeline used to generate primary test-case mapping recommendations, ensuring that every SAP Change Request receives an explicit regression determination and a contemporaneous audit record. The framework was deployed in production within a Quality Assurance Center of Excellence, processing live Change Requests across the SD, MM, FICO, TMS, and SCM modules. Evaluation demonstrated 100% coverage of regression determination across processed Change Requests, compared with a manual baseline enforcement rate of zero. An explicit no-match constraint prevented unsupported negative conclusions by flagging objects without corresponding regression-reference records for analyst review. The regression cross-check introduced zero additional analyst overhead while operating within a workflow that achieved an overall 84.6% reduction in analyst effort. During the deployment period, regression-related production defects attributable to scope gaps were eliminated, corresponding to documented annual prevention savings of USD 300,000 in defect remediation costs. The findings indicate that embedding regression verification as an unconditional pipeline control can transform a recurring process omission into an auditable compliance mechanism. However, the effectiveness and completeness of the control remain dependent on the accuracy, coverage, and ongoing maintenance of the underlying regression reference data]]>
