AI-AUGMENTED LEGACY SYSTEM INTERPRETATION: RESEARCH SUMMARY AND NEW DIRECTION

Legacy system modernization, particularly for Visual FoxPro (VFP) platforms, poses complex challenges due to the distributed and implicit nature of embedded regulatory knowledge.This research identifies and evaluates multiple interpretation methodologies, culminating in the endorsement of a Regulatory Knowledge Validation approach as the most effective strategy.Empirical evidence supports its superior accuracy-achieving 15-22% higher extraction precision-through systematic verification mechanisms.While it entails a higher upfront cost, cost-benefit analyses reveal a 47% reduction in long-term maintenance and migration expenditures. Furthermore, it effectively addresses the critical knowledge preservation risks inherentto VFP systems and optimizes expert involvement amid declining domain expertise.The validation-centric method also offers a flexible foundation for integration with other analytical techniques such as timeline alignment and pattern recognition, enabling a phased and sustainable legacy system evolution.