# DecompileBench: A Comprehensive Benchmark for Evaluating Decompilers in Real-World Scenarios

> Evaluates traditional and LLM-based decompilers using functions from real programs, runtime behavioral checks, and an LLM-assisted assessment of analyst-facing code understandability.

- Authors: Zeyu Gao; Yuxin Cui; Hao Wang; Siliang Qin; Yuanda Wang; Zhang Bolun; Chao Zhang
- Venue: Findings of ACL 2025
- Status: Conference paper
- Publication / posting date: July 2025
- Date source: ACL proceedings publication month
- First arXiv submission: May 16, 2025
- arXiv: 2505.11340
- Reviewed arXiv version: v1
- DOI: 10.18653/v1/2025.findings-acl.1194
- Sources reviewed: 2026-10-16
- Added to the catalog: 2026-10-16
- Original paper: <https://aclanthology.org/2025.findings-acl.1194/>
- PDF: <https://aclanthology.org/2025.findings-acl.1194.pdf>
- Code: <https://github.com/vul337/DecompileBench>
- BibTeX: <https://awesomerea.org/papers/citations/paper-decompilebench.bib>
- Catalog page: <https://awesomerea.org/papers/paper-decompilebench/>
- Record JSON: <https://awesomerea.org/papers/paper-decompilebench/record.json>
- Chinese version: [简体中文](https://awesomerea.org/zh/papers/paper-decompilebench/index.md)

## Scope and limitations

The evaluated corpus has 23,400 functions from 130 programs. Fuzzing-based checks have finite coverage, and understandability scores depend partly on an LLM judge. The artifact warns that rebuilt OSS-Fuzz projects can differ from the paper's versions.

## Why it fits this collection

Helps readers separate readable decompiler output from behaviorally faithful output when choosing or evaluating reverse-engineering tools.

## Publication and review notes

The published ACL record and PDF use 'Zhang Bolun'; the arXiv record uses 'Bolun Zhang'. The paper's Jennieett/DecompileBench link now redirects to vul337/DecompileBench. This is distinct from Tan et al.'s Decompile-Bench (arXiv:2505.12668).

## Primary sources

1. <https://aclanthology.org/2025.findings-acl.1194/>
2. <https://aclanthology.org/2025.findings-acl.1194.pdf>
3. <https://arxiv.org/abs/2505.11340>
4. <https://github.com/vul337/DecompileBench>
5. <https://github.com/vul337/DecompileBench/blob/761c6513b10344f502474f3e5e78c74fd89ab839/README.md>

## Related entries

- [DecompileBench (Findings of ACL 2025)](https://awesomerea.org/resources/decompilebench-paper/index.md) · Curated resource

## About this entry

Reviewed against the paper and its primary sources. Cite the original authors using the linked paper or BibTeX.
Original editorial content: MIT. Linked projects, papers and assets retain their own rights and licenses.