Do Code Clones Matter?
Not on the map. Why?
Abstract (arXiv)
Code cloning is not only assumed to inflate maintenance costs but also considered defect-prone as inconsistent changes to code duplicates can lead to unexpected behavior. Consequently, the identification of duplicated code, clone detection, has been a very active area of research in recent years. Up to now, however, no substantial investigation of the consequences of code cloning on program correctness has been carried out. To remedy this shortcoming, this paper presents the results of a large-scale case study that was undertaken to find out if inconsistent changes to cloned code can indicate faults. For the analyzed commercial and open source systems we not only found that inconsistent changes to clones are very frequent but also identified a significant number of faults induced by such changes. The clone detection tool used in the case study implements a novel algorithm for the detection of inconsistent clones. It is available as open source to enable other researchers to use it as basis for further investigations.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Jan 2017.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 3; 2025: 1; 2026: 5.
12 papers.
- 2026SlopCodeBench: Benchmarking How Coding Agents Degrade Over Long-Horizon Iterative Taskscited by 24
- 2021VELVET: a noVel Ensemble Learning approach to automatically locate VulnErable sTatementscited by 20
- 2024A Large-Scale Study of Model Integration in ML-Enabled Software Systemscited by 6
- 2026More Code, Less Reuse: Investigating Code Quality and Reviewer Sentiment towards AI-generated Pull Requestscited by 5
- 2022Eliciting Best Practices for Collaboration with Computational Notebookscited by 4
- 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
- 2026Evaluating Tool Cloning in Agentic-AI Ecosystemscited by 2
- 2024Advanced Detection of Source Code Clones via an Ensemble of Unsupervised Similarity Measurescited by 0
- 2025Auto-SPT: Automating Semantic Preserving Transformations for Codecited by 0
- 2026Super Library Agent: Joint Generation and Maintenance of Multiple Applications Beyond the Single Codebasecited by 0
- 2026ExecRetrieval: Measuring the Functional-Correctness Gap in Code-Embedding Retrievalcited by 0
- 2026ExecRetrieval: Measuring the Functional-Correctness Gap in Code-Embedding Retrieval1 Sep 2026
- 2026Super Library Agent: Joint Generation and Maintenance of Multiple Applications Beyond the Single Codebase29 Aug 2026
- 2026Evaluating Tool Cloning in Agentic-AI Ecosystems10 May 2026
- 2026SlopCodeBench: Benchmarking How Coding Agents Degrade Over Long-Horizon Iterative Tasks25 Mar 2026
- 2026More Code, Less Reuse: Investigating Code Quality and Reviewer Sentiment towards AI-generated Pull Requests29 Jan 2026
- 2025Auto-SPT: Automating Semantic Preserving Transformations for Code5 Dec 2025
- 2024A Large-Scale Study of Model Integration in ML-Enabled Software Systems12 Aug 2024
- 2024The Struggles of LLMs in Cross-lingual Code Clone Detection8 Aug 2024
- 2024Advanced Detection of Source Code Clones via an Ensemble of Unsupervised Similarity Measures3 May 2024
- 2023Unveiling the potential of large language models in generating semantic and cross-language clones12 Sep 2023
- 2022Eliciting Best Practices for Collaboration with Computational Notebooks15 Feb 2022
- 2021VELVET: a noVel Ensemble Learning approach to automatically locate VulnErable sTatements20 Dec 2021