C2RUST-BENCH: A Minimized, Representative Dataset for C-to-Rust Transpilation Evaluation
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866916699607924736 |
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| author | Sirlanci, Melih Yagemann, Carter Lin, Zhiqiang |
| author_facet | Sirlanci, Melih Yagemann, Carter Lin, Zhiqiang |
| contents | Despite the effort in vulnerability detection over the last two decades, memory safety vulnerabilities continue to be a critical problem. Recent reports suggest that the key solution is to migrate to memory-safe languages. To this end, C-to-Rust transpilation becomes popular to resolve memory-safety issues in C programs. Recent works propose C-to-Rust transpilation frameworks; however, a comprehensive evaluation dataset is missing. Although one solution is to put together a large enough dataset, this increases the analysis time in automated frameworks as well as in manual efforts for some cases. In this work, we build a method to select functions from a large set to construct a minimized yet representative dataset to evaluate the C-to-Rust transpilation. We propose C2RUST-BENCH that contains 2,905 functions, which are representative of C-to-Rust transpilation, selected from 15,503 functions of real-world programs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_15144 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | C2RUST-BENCH: A Minimized, Representative Dataset for C-to-Rust Transpilation Evaluation Sirlanci, Melih Yagemann, Carter Lin, Zhiqiang Cryptography and Security Artificial Intelligence Programming Languages Despite the effort in vulnerability detection over the last two decades, memory safety vulnerabilities continue to be a critical problem. Recent reports suggest that the key solution is to migrate to memory-safe languages. To this end, C-to-Rust transpilation becomes popular to resolve memory-safety issues in C programs. Recent works propose C-to-Rust transpilation frameworks; however, a comprehensive evaluation dataset is missing. Although one solution is to put together a large enough dataset, this increases the analysis time in automated frameworks as well as in manual efforts for some cases. In this work, we build a method to select functions from a large set to construct a minimized yet representative dataset to evaluate the C-to-Rust transpilation. We propose C2RUST-BENCH that contains 2,905 functions, which are representative of C-to-Rust transpilation, selected from 15,503 functions of real-world programs. |
| title | C2RUST-BENCH: A Minimized, Representative Dataset for C-to-Rust Transpilation Evaluation |
| topic | Cryptography and Security Artificial Intelligence Programming Languages |
| url | https://arxiv.org/abs/2504.15144 |