RustAssure: Differential Symbolic Testing for LLM-Transpiled C-to-Rust Code
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866916997928845312 |
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| author | Bai, Yubo Palit, Tapti |
| author_facet | Bai, Yubo Palit, Tapti |
| contents | Rust is a memory-safe programming language that significantly improves software security. Existing codebases written in unsafe memory languages, such as C, must first be transpiled to Rust to take advantage of Rust's improved safety guarantees. RustAssure presents a system that uses Large Language Models (LLMs) to automatically transpile existing C codebases to Rust. RustAssure uses prompt engineering techniques to maximize the chances of the LLM generating idiomatic and safe Rust code. Moreover, because LLMs often generate code with subtle bugs that can be missed under traditional unit or fuzz testing, RustAssure performs differential symbolic testing to establish the semantic similarity between the original C and LLM-transpiled Rust code. We evaluated RustAssure with five real-world applications and libraries, and showed that our system is able to generate compilable Rust functions for 89.8% of all C functions, of which 69.9% produced equivalent symbolic return values for both the C and Rust functions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_07604 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | RustAssure: Differential Symbolic Testing for LLM-Transpiled C-to-Rust Code Bai, Yubo Palit, Tapti Software Engineering D.2.4 Rust is a memory-safe programming language that significantly improves software security. Existing codebases written in unsafe memory languages, such as C, must first be transpiled to Rust to take advantage of Rust's improved safety guarantees. RustAssure presents a system that uses Large Language Models (LLMs) to automatically transpile existing C codebases to Rust. RustAssure uses prompt engineering techniques to maximize the chances of the LLM generating idiomatic and safe Rust code. Moreover, because LLMs often generate code with subtle bugs that can be missed under traditional unit or fuzz testing, RustAssure performs differential symbolic testing to establish the semantic similarity between the original C and LLM-transpiled Rust code. We evaluated RustAssure with five real-world applications and libraries, and showed that our system is able to generate compilable Rust functions for 89.8% of all C functions, of which 69.9% produced equivalent symbolic return values for both the C and Rust functions. |
| title | RustAssure: Differential Symbolic Testing for LLM-Transpiled C-to-Rust Code |
| topic | Software Engineering D.2.4 |
| url | https://arxiv.org/abs/2510.07604 |