A Survey of Symbol Name Recovery in Software Reverse Engineering

Reading the original semantics from symbol-stripped binaries, symbol-stripped bytecode, or symbol-stripped source code is challenging because high-level information, such as function and variable names, is unavailable. Recovering these names is crucial to understanding software behavior and enabling security applications. Previous work has shown that lost symbol names can be recovered, leading many researchers to propose approaches for name recovery. This work presents a systematic survey to examine the significance, existing methodologies, implementations, and evaluations. Additionally, the study discusses insights gained from the systematization, highlights remaining challenges, and offers thoughts on future research directions.

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Publication Details

Journal
ACM Computing Surveys
Published
2026-09-01
DOI
https://doi.org/10.1145/3844948
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

A Survey of Symbol Name Recovery in Software Reverse Engineering

Xincheng He, Qingkai Shi, Yibiao Yang, Yang Feng et al.
ACM Computing Surveys
Advanced Malware Detection Techniques
article

A Survey of Symbol Name Recovery in Software Reverse Engineering

Xincheng He, Qingkai Shi, Yibiao Yang, Yang Feng, Baowen Xu, Jian Wu, Hongcheng Fan
article en

Abstract

Reading the original semantics from symbol-stripped binaries, symbol-stripped bytecode, or symbol-stripped source code is challenging because high-level information, such as function and variable names, is unavailable. Recovering these names is crucial to understanding software behavior and enabling security applications. Previous work has shown that lost symbol names can be recovered, leading many researchers to propose approaches for name recovery. This work presents a systematic survey to examine the significance, existing methodologies, implementations, and evaluations. Additionally, the study discusses insights gained from the systematization, highlights remaining challenges, and offers thoughts on future research directions.

ACM Computing Surveys
Nanjing University (CN)
Openalex Percentile: Top 9%
Advanced Malware Detection Techniques
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