{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/decompilebench-a-comprehensive-benchmark-for","title":"DecompileBench: A Comprehensive Benchmark for Evaluating Decompilers in Real-World Scenarios","arxiv_id":"2505.11340","date":"2025-05-16","proceeding":null,"authors":["Zeyu Gao","Yuxin Cui","Hao Wang","Siliang Qin","Yuanda Wang","Bolun Zhang","Chao Zhang"],"abstract":"Decompilers are fundamental tools for critical security tasks, from vulnerability discovery to malware analysis, yet their evaluation remains fragmented. Existing approaches primarily focus on syntactic correctness through synthetic micro-benchmarks or subjective human ratings, failing to address real-world requirements for semantic fidelity and analyst usability. We present DecompileBench, the first comprehensive framework that enables effective evaluation of decompilers in reverse engineering workflows through three key components: \\textit{real-world function extraction} (comprising 23,400 functions from 130 real-world programs), \\textit{runtime-aware validation}, and \\textit{automated human-centric assessment} using LLM-as-Judge to quantify the effectiveness of decompilers in reverse engineering workflows. Through a systematic comparison between six industrial-strength decompilers and six recent LLM-powered approaches, we demonstrate that LLM-based methods surpass commercial tools in code understandability despite 52.2% lower functionality correctness. These findings highlight the potential of LLM-based approaches to transform human-centric reverse engineering. We open source \\href{https://github.com/Jennieett/DecompileBench}{DecompileBench} to provide a framework to advance research on decompilers and assist security experts in making informed tool selections based on their specific requirements.","url_abs":"https://arxiv.org/abs/2505.11340v1","url_pdf":"https://arxiv.org/pdf/2505.11340v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"decompilebench-a-comprehensive-benchmark-for","repo_url":"https://github.com/jennieett/decompilebench","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"malware-analysis","task_name":"Malware Analysis"}],"methods":[{"method_slug":"focus","method_name":"Focus"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}