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Fixing Rust Compilation Errors using LLMs

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arxiv 2308.05177 v1 pith:ZZCRQ4XX submitted 2023-08-09 cs.SE cs.PL

Fixing Rust Compilation Errors using LLMs

classification cs.SE cs.PL
keywords rustcompilationerrorslanguagerustassistantaccuracyfeaturesfixes
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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The Rust programming language, with its safety guarantees, has established itself as a viable choice for low-level systems programming language over the traditional, unsafe alternatives like C/C++. These guarantees come from a strong ownership-based type system, as well as primitive support for features like closures, pattern matching, etc., that make the code more concise and amenable to reasoning. These unique Rust features also pose a steep learning curve for programmers. This paper presents a tool called RustAssistant that leverages the emergent capabilities of Large Language Models (LLMs) to automatically suggest fixes for Rust compilation errors. RustAssistant uses a careful combination of prompting techniques as well as iteration with an LLM to deliver high accuracy of fixes. RustAssistant is able to achieve an impressive peak accuracy of roughly 74% on real-world compilation errors in popular open-source Rust repositories. We plan to release our dataset of Rust compilation errors to enable further research.

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Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Rover: Context-aware Conflict Resolution with LLM

    cs.SE 2026-05 unverdicted novelty 7.0

    Rover uses a new Multi-layer Code Property Graph and clustering to supply LLMs with dependency-aware contexts, outperforming standalone LLMs, MergeGen, and WizardMerge on similarity to ground-truth conflict resolutions.

  2. An End-to-End Approach for Fixing Concurrency Bugs via SHB-Based Context Extractor

    cs.SE 2026-04 unverdicted novelty 7.0

    ConFixAgent repairs diverse concurrency bugs end-to-end by using Static Happens-Before graphs to extract relevant code context for LLMs, outperforming prior tools in benchmarks.

  3. SafeTrans: LLM-assisted Transpilation from C to Rust

    cs.CR 2025-05 accept novelty 6.0

    SafeTrans achieves up to 80% successful C-to-Rust translations via LLM iterative repair on 2653 programs and two real projects, with some C vulnerabilities carrying over to the Rust output.

  4. TransAgent: Enhancing LLM-Based Code Translation via Fine-Grained Execution Alignment

    cs.SE 2024-09 unverdicted novelty 5.0

    TransAgent improves LLM code translation by up to 33.3% via multi-agent fine-grained execution alignment on a new benchmark of recent tasks.