# Project-Level C-to-Rust Translation via Pointer Knowledge Graphs

arXiv: https://arxiv.org/abs/2510.10956 · HTML: https://mlsanity.com/paper/2510.10956/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 21 of its 72 references that are in the map.
- First posted on arXiv 13 Oct 2025.

## Builds on (most cited first, 21 of 21)

- [CodeBLEU: a Method for Automatic Evaluation of Code Synthesis](https://mlsanity.com/paper/2009.10297/) (2020)
- [Unsupervised Translation of Programming Languages](https://mlsanity.com/paper/2006.03511/) (2020)
- [Self-collaboration Code Generation via ChatGPT](https://mlsanity.com/paper/2304.07590/) (2023)
- [RepairAgent: An Autonomous, LLM-Based Agent for Program Repair](https://mlsanity.com/paper/2403.17134/) (2024)
- [CodeTransOcean: A Comprehensive Multilingual Benchmark for Code Translation](https://mlsanity.com/paper/2310.04951/) (2023)
- [Exploring and Unleashing the Power of Large Language Models in Automated Code Translation](https://mlsanity.com/paper/2404.14646/) (2024)
- [Evaluating Instruction-Tuned Large Language Models on Code Comprehension and Generation](https://mlsanity.com/paper/2308.01240/) (2023)
- [Towards Translating Real-World Code with LLMs: A Study of Translating to Rust](https://mlsanity.com/paper/2405.11514/) (2024)
- [AlphaTrans: A Neuro-Symbolic Compositional Approach for Repository-Level Code Translation and Validation](https://mlsanity.com/paper/2410.24117/) (2024)
- [CRUST-Bench: A Comprehensive Benchmark for C-to-safe-Rust Transpilation](https://mlsanity.com/paper/2504.15254/) (2025)
- [C2SaferRust: Transforming C Projects into Safer Rust with NeuroSymbolic Techniques](https://mlsanity.com/paper/2501.14257/) (2025)
- [Syzygy: Dual Code-Test C to (safe) Rust Translation using LLMs and Dynamic Analysis](https://mlsanity.com/paper/2412.14234/) (2024)
- [Ownership guided C to Rust translation](https://mlsanity.com/paper/2303.10515/) (2023)
- [Scalable, Validated Code Translation of Entire Projects using Large Language Models](https://mlsanity.com/paper/2412.08035/) (2024)
- [RustMap: Towards Project-Scale C-to-Rust Migration via Program Analysis and LLM](https://mlsanity.com/paper/2503.17741/) (2025)
- [To Tag, or Not to Tag: Translating C's Unions to Rust's Tagged Unions](https://mlsanity.com/paper/2408.11418/) (2024)
- [Translating C To Rust: Lessons from a User Study](https://mlsanity.com/paper/2411.14174/) (2024)
- [SafeTrans: LLM-assisted Transpilation from C to Rust](https://mlsanity.com/paper/2505.10708/) (2025)
- [A Closer Look at the Security Risks in the Rust Ecosystem](https://mlsanity.com/paper/2308.15046/) (2023)
- [RepoTransAgent: Multi-Agent LLM Framework for Repository-Aware Code Translation](https://mlsanity.com/paper/2508.17720/) (2025)
- [How ISO C became unusable for operating systems development](https://mlsanity.com/paper/2201.07845/) (2022)

## Built on by (most cited first, 3 of 3)

- [ReCodeAgent: A Multi-agent Workflow for Language-Agnostic Translation and Validation of Large-Scale Repositories](https://mlsanity.com/paper/2604.07341/) (2026)
- [CodePivot: Bootstrapping Multilingual Transpilation in LLMs via Reinforcement Learning without Parallel Corpora](https://mlsanity.com/paper/2604.18027/) (2026)
- [Translator vs. Challenger: Adversarial Agentic Learning for C-to-Rust Translation](https://mlsanity.com/paper/2609.15381/) (2026)

## Abstract (arXiv)

Translating C code into safe Rust is an effective way to ensure memory safety. Compared to rule-based approaches, which often produce largely unsafe Rust code, LLM-based methods generate more idiomatic and safer Rust by leveraging extensive training on human-written code. Despite their promise, existing LLM-based approaches still struggle with project-level C-to-Rust translation. They typically partition a C project into smaller units (e.g., functions) based on call graphs and translate them in a bottom-up manner to resolve dependencies. However, this unit-by-unit paradigm often fails to handle pointers due to the lack of a global view of their usage. To address this limitation, we propose a novel C-to-Rust Pointer Knowledge Graph (KG) that augments code dependency graphs with two types of pointer semantics: (i) pointer usage information, which captures global behaviors such as points-to flows and lifts low-level struct interactions to higher-level abstractions; and (ii) Rust-oriented annotations, which encode ownership, mutability, nullability, and lifetime. Building on this KG, we further propose PtrTrans, a project-level C-to-Rust translation approach. In PtrTrans, the KG provides LLMs with comprehensive global pointer semantics, guiding them to generate safe and idiomatic Rust code. Experimental results show that PtrTrans reduces unsafe usages in translated Rust by 99.9% compared to both rule-based and conventional LLM-based methods, while achieving 29.3% higher functional correctness than fuzzing-enhanced LLM approaches.