Translating Large-Scale C Repositories to Idiomatic Rust
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Abstract (arXiv)
Existing C to Rust translation techniques fail to balance quality and scalability: transpilation-based approaches scale to large projects but produce code with poor safety, idiomaticity, and readability. In contrast, LLM-based techniques are prohibitively expensive due to their reliance on frontier models (without which they cannot reliably generate compilable translations), thus limiting scalability. This paper proposes Rustine, a fully automated pipeline for effective and efficient repository-level C to idiomatic safe Rust translation. Evaluating on a diverse set of 23 C programs, ranging from 27 to 13,200 lines of code, Rustine can generate fully compilable Rust code for all and achieve 87% functional equivalence (passing 1,063,099 assertions out of 1,221,192 in test suites with average function and line coverage of 74.7% and 72.2%). Compared to six prior repository-level C to Rust translation techniques, the translations by Rustine are overall safer (fewer raw pointers, pointer arithmetic, and unsafe constructs), more idiomatic (fewer Rust linter violations), and more readable. When the translations cannot pass all tests to fulfill functional equivalence, human developers were able to complete the task in 4.5 hours, on average, using Rustine as debugging support.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 25 Nov 2025.
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Citing papers per year: 2026: 6.
6 papers.
- 2026ENCRUST: Encapsulated Substitution and Agentic Refinement on a Live Scaffold for Safe C-to-Rust Translationcited by 2
- 2026ReCodeAgent: A Multi-agent Workflow for Language-Agnostic Translation and Validation of Large-Scale Repositoriescited by 2
- 2026His2Trans: A Knowledge-Guided Agentic Framework for Project-Level C-to-Rust Migrationcited by 1
- 2026SPARC: Scenario Planning and Reasoning for Automated C Unit Test Generationcited by 0
- 2026Documentation-Guided Agentic Codebase Migration from C to Rustcited by 0
- 2026Translator vs. Challenger: Adversarial Agentic Learning for C-to-Rust Translationcited by 0
- 2026Translator vs. Challenger: Adversarial Agentic Learning for C-to-Rust Translation14 Sep 2026
- 2026Documentation-Guided Agentic Codebase Migration from C to Rust14 May 2026
- 2026ReCodeAgent: A Multi-agent Workflow for Language-Agnostic Translation and Validation of Large-Scale Repositories8 Apr 2026
- 2026ENCRUST: Encapsulated Substitution and Agentic Refinement on a Live Scaffold for Safe C-to-Rust Translation6 Apr 2026
- 2026His2Trans: A Knowledge-Guided Agentic Framework for Project-Level C-to-Rust Migration3 Mar 2026
- 2026SPARC: Scenario Planning and Reasoning for Automated C Unit Test Generation18 Feb 2026