Oreo: Detection of Clones in the Twilight Zone
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Abstract (arXiv)
Source code clones are categorized into four types of increasing difficulty of detection, ranging from purely textual (Type-1) to purely semantic (Type-4). Most clone detectors reported in the literature work well up to Type-3, which accounts for syntactic differences. In between Type-3 and Type-4, however, there lies a spectrum of clones that, although still exhibiting some syntactic similarities, are extremely hard to detect -- the Twilight Zone. Most clone detectors reported in the literature fail to operate in this zone. We present Oreo, a novel approach to source code clone detection that not only detects Type-1 to Type-3 clones accurately, but is also capable of detecting harder-to-detect clones in the Twilight Zone. Oreo is built using a combination of machine learning, information retrieval, and software metrics. We evaluate the recall of Oreo on BigCloneBench, and perform manual evaluation for precision. Oreo has both high recall and precision. More importantly, it pushes the boundary in detection of clones with moderate to weak syntactic similarity in a scalable manner.
Key facts. Cited by 19 papers in the map (data through 14 Oct 2026). First posted on arXiv 15 Jun 2018.
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Citing papers per year: 2021: 5; 2022: 2; 2023: 4; 2024: 2; 2025: 4; 2026: 2.
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- 2023Trustworthy and Synergistic Artificial Intelligence for Software Engineering: Vision and Roadmapscited by 19
- 2023A systematic literature review on source code similarity measurement and clone detection: techniques, applications, and challengescited by 14
- 2022AutoPruner: Transformer-Based Call Graph Pruningcited by 11
- 2021A Comprehensive Survey of Logging in Software: From Logging Statements Automation to Log Mining and Analysiscited by 6
- 2025Chain-of-Descriptions: Improving Code LLMs for VHDL Code Generation and Summarizationcited by 6
- 2022Generalizability of Code Clone Detection on CodeBERTcited by 4
- 2023TransformCode: A Contrastive Learning Framework for Code Embedding via Subtree Transformationcited by 4
- 2021Senatus -- A Fast and Accurate Code-to-Code Recommendation Enginecited by 3
- 2023Unveiling the potential of large language models in generating semantic and cross-language clonescited by 3
- 2024The Struggles of LLMs in Cross-lingual Code Clone Detectioncited by 3
- 2021Leveraging Code Clones and Natural Language Processing for Log Statement Predictioncited by 1
- 2021Code Clone Detection based on Event Embedding and Event Dependencycited by 1
7 more
- 2024Assessing the Code Clone Detection Capability of Large Language Modelscited by 1
- 2025Call Me Maybe: Enhancing JavaScript Call Graph Construction using Graph Neural Networkscited by 1
- 2025Previously on... Automating Code Reviewcited by 1
- 2021Borrowing from Similar Code: A Deep Learning NLP-Based Approach for Log Statement Automationcited by 0
- 2025Selecting and Combining Large Language Models for Scalable Code Clone Detectioncited by 0
- 2026Given, When, Then, Again: Mining Subscenario Refactoring Candidates in Behaviour-Driven Test Suites with ML Classifiers and LLM-Judge Baselinescited by 0
- 2026Super Library Agent: Joint Generation and Maintenance of Multiple Applications Beyond the Single Codebasecited by 0
- 2026Super Library Agent: Joint Generation and Maintenance of Multiple Applications Beyond the Single Codebase29 Aug 2026
- 2026Given, When, Then, Again: Mining Subscenario Refactoring Candidates in Behaviour-Driven Test Suites with ML Classifiers and LLM-Judge Baselines14 May 2026
- 2025Selecting and Combining Large Language Models for Scalable Code Clone Detection17 Oct 2025
- 2025Previously on... Automating Code Review25 Aug 2025
- 2025Chain-of-Descriptions: Improving Code LLMs for VHDL Code Generation and Summarization16 Jul 2025
- 2025Call Me Maybe: Enhancing JavaScript Call Graph Construction using Graph Neural Networks22 Jun 2025
- 2024The Struggles of LLMs in Cross-lingual Code Clone Detection8 Aug 2024
- 2024Assessing the Code Clone Detection Capability of Large Language Models2 Jul 2024
- 2023TransformCode: A Contrastive Learning Framework for Code Embedding via Subtree Transformation10 Nov 2023
- 2023Unveiling the potential of large language models in generating semantic and cross-language clones12 Sep 2023
- 2023Trustworthy and Synergistic Artificial Intelligence for Software Engineering: Vision and Roadmaps8 Sep 2023
- 2023A systematic literature review on source code similarity measurement and clone detection: techniques, applications, and challenges28 Jun 2023
7 more
- 2022AutoPruner: Transformer-Based Call Graph Pruning7 Sep 2022
- 2022Generalizability of Code Clone Detection on CodeBERT26 Aug 2022
- 2021Borrowing from Similar Code: A Deep Learning NLP-Based Approach for Log Statement Automation2 Dec 2021
- 2021Code Clone Detection based on Event Embedding and Event Dependency28 Nov 2021
- 2021Senatus -- A Fast and Accurate Code-to-Code Recommendation Engine5 Nov 2021
- 2021A Comprehensive Survey of Logging in Software: From Logging Statements Automation to Log Mining and Analysis24 Oct 2021
- 2021Leveraging Code Clones and Natural Language Processing for Log Statement Prediction8 Sep 2021
- 2023Trustworthy and Synergistic Artificial Intelligence for Software Engineering: Vision and Roadmapscited by 19
- 2023A systematic literature review on source code similarity measurement and clone detection: techniques, applications, and challengescited by 14
- 2022AutoPruner: Transformer-Based Call Graph Pruningcited by 11
- 2021A Comprehensive Survey of Logging in Software: From Logging Statements Automation to Log Mining and Analysiscited by 6
- 2025Chain-of-Descriptions: Improving Code LLMs for VHDL Code Generation and Summarizationcited by 6
- 2022Generalizability of Code Clone Detection on CodeBERTcited by 4
- 2023TransformCode: A Contrastive Learning Framework for Code Embedding via Subtree Transformationcited by 4
- 2021Senatus -- A Fast and Accurate Code-to-Code Recommendation Enginecited by 3
- 2023Unveiling the potential of large language models in generating semantic and cross-language clonescited by 3
- 2024The Struggles of LLMs in Cross-lingual Code Clone Detectioncited by 3
- 2021Leveraging Code Clones and Natural Language Processing for Log Statement Predictioncited by 1
- 2021Code Clone Detection based on Event Embedding and Event Dependencycited by 1
12 most cited of 18 All 18 (JSON)
- 2026Given, When, Then, Again: Mining Subscenario Refactoring Candidates in Behaviour-Driven Test Suites with ML Classifiers and LLM-Judge Baselines14 May 2026
- 2025Selecting and Combining Large Language Models for Scalable Code Clone Detection17 Oct 2025
- 2025Previously on... Automating Code Review25 Aug 2025
- 2025Chain-of-Descriptions: Improving Code LLMs for VHDL Code Generation and Summarization16 Jul 2025
- 2025Call Me Maybe: Enhancing JavaScript Call Graph Construction using Graph Neural Networks22 Jun 2025
- 2024The Struggles of LLMs in Cross-lingual Code Clone Detection8 Aug 2024
- 2024Assessing the Code Clone Detection Capability of Large Language Models2 Jul 2024
- 2023TransformCode: A Contrastive Learning Framework for Code Embedding via Subtree Transformation10 Nov 2023
- 2023Unveiling the potential of large language models in generating semantic and cross-language clones12 Sep 2023
- 2023Trustworthy and Synergistic Artificial Intelligence for Software Engineering: Vision and Roadmaps8 Sep 2023
- 2023A systematic literature review on source code similarity measurement and clone detection: techniques, applications, and challenges28 Jun 2023
- 2022AutoPruner: Transformer-Based Call Graph Pruning7 Sep 2022
12 newest of 18 All 18 (JSON)