Code Translation

Code translation aims to automatically convert code between programming languages while preserving functionality, crucial for software modernization and cross-platform development. Current research heavily utilizes large language models (LLMs), often incorporating techniques like retrieval-augmented generation, multi-agent systems, and reinforcement learning with compiler feedback to improve translation accuracy and address issues like syntax and semantic errors. These advancements are improving the reliability and efficiency of code translation, impacting software engineering practices by streamlining code migration and facilitating interoperability across different programming languages. Furthermore, research is exploring the use of intermediate representations and improved evaluation metrics to enhance the robustness and reliability of automated code translation systems.