SAS-to-Python Translator is an interactive, research-driven application designed to demonstrate how artificial intelligence can translate, interpret, and modernize legacy SAS programs into equivalent Python implementations. The system moves beyond rule-based code conversion by leveraging semantic analysis, structural mapping, and context-aware transformation techniques to preserve computational intent, data workflows, and statistical logic across languages. This enables more reliable and maintainable migration compared to traditional line-by-line or syntax-only translators.
The platform serves both as a practical conversion tool and as a research prototype for studying cross-language program understanding, legacy system modernization, and automated refactoring. It can be used to explore how procedural data steps, macro logic, and statistical procedures in SAS map onto Python ecosystems such as pandas, NumPy, and SciPy, making it valuable for enterprise migration, reproducible analytics, regulatory modernization, and technical debt reduction.
In addition, the system provides a foundation for extending code translation toward verification-aware and explainable frameworks, where generated Python code can be validated against original SAS outputs and annotated to improve transparency and trust. This makes the project suitable for benchmarking automated migration approaches, integrating into modernization pipelines, or supporting large-scale transitions from proprietary analytics platforms to open-source environments.
You can explore the live interactive demo: [Demo]
This project reflects ongoing work in automated code translation, program analysis, and AI-assisted software modernization, and can serve as a starting point for research extensions, enterprise adoption, or integration into broader AI-enabled development systems.
