Research Progress and Challenges in Code Translation for the Rust Language

With the growing adoption of Rust in operating systems, platform software, and infrastructure software, how to migrate existing software assets into the Rust ecosystem has become an important problem with both industrial and research significance. Code translation for Rust is evolving from traditional source-to-source transformation into a systematic approach to software migration. This article first analyzes the technical background of Rust and the practical motivations for evolving existing systems toward Rust, and then explains the value of code translation in preserving software assets, realizing Rust’s safety benefits, and supporting controlled software evolution. It further reviews current research progress from four perspectives: rule-based translation, direct translation based on large language models, analysis-enhanced neuro-symbolic translation, and project-level incremental migration. On this basis, it summarizes key challenges including semantic preservation, Rust-oriented reconstruction, third-party dependency migration, complex system coupling, result validation, and project-level context organization, and discusses future development trends. Overall, code translation for Rust is moving from code conversion toward software migration, becoming an important technical direction that connects language evolution, software engineering, and the reconstruction of infrastructure software ecosystems.