mlsanityData to 7 Oct 2026

A Survey of Binary Code Similarity

arXiv 1909.11424 ↗First posted 25 Sep 2019cs.CRcited by 18

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Abstract (arXiv)

Binary code similarity approaches compare two or more pieces of binary code to identify their similarities and differences. The ability to compare binary code enables many real-world applications on scenarios where source code may not be available such as patch analysis, bug search, and malware detection and analysis. Over the past 20 years numerous binary code similarity approaches have been proposed, but the research area has not yet been systematically analyzed. This paper presents a first survey of binary code similarity. It analyzes 61 binary code similarity approaches, which are systematized on four aspects: (1) the applications they enable, (2) their approach characteristics, (3) how the approaches are implemented, and (4) the benchmarks and methodologies used to evaluate them. In addition, the survey discusses the scope and origins of the area, its evolution over the past two decades, and the challenges that lie ahead.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). First posted on arXiv 25 Sep 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 4; 2022: 4; 2023: 3; 2024: 1; 2025: 1; 2026: 5.

18 papers.

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  1. 2021ModelDiff: Testing-Based DNN Similarity Comparison for Model Reuse Detectioncited by 33
  2. 2025Large Language Models (LLMs) for Source Code Analysis: applications, models and datasetscited by 15
  3. 2024Vi(E)va LLM! A Conceptual Stack for Evaluating and Interpreting Generative AI-based Visualizationscited by 10
  4. 2021Semantic-aware Binary Code Representation with BERTcited by 6
  5. 2022Pre-Training Representations of Binary Code Using Contrastive Learningcited by 6
  6. 2022Deep-Learning-based Vulnerability Detection in Binary Executablescited by 6
  7. 2023EMBERSim: A Large-Scale Databank for Boosting Similarity Search in Malware Analysiscited by 6
  8. 2021Predicting Patch Correctness Based on the Similarity of Failing Test Casescited by 4
  9. 2022FuncFooler: A Practical Black-box Attack Against Learning-based Binary Code Similarity Detection Methodscited by 3
  10. 2023VEXIR2Vec: An Architecture-Neutral Embedding Framework for Binary Similaritycited by 1
  11. 2026Fool Me If You Can: On the Robustness of Binary Code Similarity Detection Models against Semantics-preserving Transformationscited by 1
  12. 2021Binary Diffing as a Network Alignment Problem via Belief Propagationcited by 0
6 more
  1. 2022SimCLF: A Simple Contrastive Learning Framework for Function-level Binary Embeddingscited by 0
  2. 2023Pluvio: Assembly Clone Search for Out-of-domain Architectures and Libraries through Transfer Learning and Conditional Variational Information Bottleneckcited by 0
  3. 2026A Unified Evaluation of Learning-Based Similarity Techniques for Malware Detectioncited by 0
  4. 2026EXHIB: A Benchmark for Realistic and Diverse Evaluation of Function Similarity in the Wildcited by 0
  5. 2026SoK: AI-Augmented Binary Reversingcited by 0
  6. 2026Instruction Alignment for Binary Code Representation Learningcited by 0