arXiv subjects

Yunbo Ni

Publications and source records attributed to Yunbo Ni.

4 recordsLinked to original sources

arXiv2026

Archer: Towards Agentic Review for Compiler Optimizations

Modern compilers are frequently updated, but expert review capacity is highly limited, leading to delayed integration and, in some cases, subtle semantic bugs entering the compiler codebase. Automating the code review process with modern general code review agents may be feasible, but it faces critical challenges due to compiler complexity. In this paper, we use LLVM as our target compiler and present Archer, the first automated agentic code review tool for compiler optimizations. Archer constrains the agentic review process from both ends by using obligations to guide analysis and a deterministic validation guard to admit only findings backed by executable evidence. We evaluated Archer on 70 open PRs and 328 closed PRs in LLVM from the last two months. The review results are shocking and concerning: Archer discovers that 21% of open PRs and 11% of closed PRs are buggy, i.e, introducing semantic bugs such as miscompilations in LLVM. Our findings expose a critical gap in the capacity for critical review in large compiler projects and demonstrate the practical value of Archer as an additional reviewer.

cs.SE↗

arXiv2025

Interleaving Large Language Models for Compiler Testing

Testing compilers with AI models, especially large language models (LLMs), has shown great promise. However, current approaches struggle with two key problems: The generated programs for testing compilers are often too simple, and extensive testing with the LLMs is computationally expensive. In this paper, we propose a novel compiler testing framework that decouples the testing process into two distinct phases: an offline phase and an online phase. In the offline phase, we use LLMs to generate a collection of small but feature-rich code pieces. In the online phase, we reuse these code pieces by strategically combining them to build high-quality and valid test programs, which are then used to test compilers. We implement this idea in a tool, LegoFuzz, for testing C compilers. The results are striking: we found 66 bugs in GCC and LLVM, the most widely used C compilers. Almost half of the bugs are miscompilation bugs, which are serious and hard-to-find bugs that none of the existing LLM-based tools could find. We believe this efficient design opens up new possibilities for using AI models in software testing beyond just C compilers.

cs.SE↗

arXiv2025

An Empirical Study of Rust-Specific Bugs in the rustc Compiler

Rust is gaining popularity for its well-known memory safety guarantees and high performance, distinguishing it from C/C++ and JVM-based languages. Its compiler, rustc, enforces these guarantees through specialized mechanisms such as trait solving, borrow checking, and specific optimizations. However, Rust's unique language mechanisms introduce complexity to its compiler, leading to Rust-specific compiler bugs that are less common in traditional compilers. With Rust's increasing adoption in safety-critical domains, understanding these language mechanisms and their impact on compiler bugs is essential for improving the reliability of both rustc and Rust programs. Yet, we still lack a large-scale, detailed, and in-depth study of Rust-specific bugs in rustc. To bridge this gap, this work conducts a comprehensive and systematic study of Rust-specific bugs in rustc, with a particular focus on the components that support its unique language features. Our analysis examines issues and fixes reported between 2022 and 2024, with a manual review of 301 valid issues. We categorize these bugs based on their causes, symptoms, affected compilation stages, and test case characteristics. Additionally, we evaluate existing rustc testing tools to assess their effectiveness and limitations. Our key findings include: (1) rustc bugs primarily arise from Rust's type system and lifetime model, with frequent errors in the High-Level Intermediate Representation (HIR) and Mid-Level Intermediate Representation (MIR) modules due to complex checkers and optimizations; (2) bug-revealing test cases often involve unstable features, advanced trait usages, lifetime annotations, standard APIs, and specific optimization levels; (3) while both valid and invalid programs can trigger bugs, existing testing tools struggle to detect non-crash errors, underscoring the need for further advancements in rustc testing.

cs.PL↗

arXiv2024

PanicFI: An Infrastructure for Fixing Panic Bugs in Real-World Rust Programs

The Rust programming language has garnered significant attention due to its robust safety features and memory management capabilities. Despite its guaranteed memory safety, Rust programs suffer from runtime errors that are unmanageable, i.e., panic errors. Notably, traditional memory issues such as null pointer dereferences, which are prevalent in other languages, are less likely to be triggered in Rust due to its strict ownership rules. However, the unique nature of Rust's panic bugs, which arise from the language's stringent safety and ownership paradigms, presents a distinct challenge. Over half of the bugs in rustc, Rust's own compiler, are attributable to crash stemming from panic errors. However, addressing Rust panic bugs is challenging and requires significant effort, as existing fix patterns are not directly applicable due to the design and feature of Rust language.Therefore, developing foundational infrastructure, including datasets, fixing patterns, and automated repair tools, is both critical and urgent. This paper introduces a comprehensive infrastructure, namely PanicFI, aimed at providing supports for understanding Rust panic bugs and developing automated techniques. In PanicFI, we construct a dataset, Panic4R, comprising 102 real panic bugs and their fixes from the top 500 most-downloaded open-source crates.Then, through an analysis of the Rust compiler implementation , we identify Rust-specific patterns for fixing panic bugs, providing insights and guidance for generating patches. Moreover, we develop PanicKiller, the first automated tool for fixing Rust panic bugs, which has already contributed to the resolution of 28 panic bugs in open-source projects.The practicality and efficiency of PanicKiller confirm the effectiveness of the patterns mined within PanicFI.

cs.SE↗