# Do Code Clones Matter?

arXiv: https://arxiv.org/abs/1701.05472 · HTML: https://mlsanity.com/paper/1701.05472/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Jan 2017.

## Built on by (most cited first, 12 of 12)

- [SlopCodeBench: Benchmarking How Coding Agents Degrade Over Long-Horizon Iterative Tasks](https://mlsanity.com/paper/2603.24755/) (2026)
- [VELVET: a noVel Ensemble Learning approach to automatically locate VulnErable sTatements](https://mlsanity.com/paper/2112.10893/) (2021)
- [More Code, Less Reuse: Investigating Code Quality and Reviewer Sentiment towards AI-generated Pull Requests](https://mlsanity.com/paper/2601.21276/) (2026)
- [A Large-Scale Study of Model Integration in ML-Enabled Software Systems](https://mlsanity.com/paper/2408.06226/) (2024)
- [Eliciting Best Practices for Collaboration with Computational Notebooks](https://mlsanity.com/paper/2202.07233/) (2022)
- [Unveiling the potential of large language models in generating semantic and cross-language clones](https://mlsanity.com/paper/2309.06424/) (2023)
- [The Struggles of LLMs in Cross-lingual Code Clone Detection](https://mlsanity.com/paper/2408.04430/) (2024)
- [Evaluating Tool Cloning in Agentic-AI Ecosystems](https://mlsanity.com/paper/2605.09817/) (2026)
- [Auto-SPT: Automating Semantic Preserving Transformations for Code](https://mlsanity.com/paper/2512.06042/) (2025)
- [Advanced Detection of Source Code Clones via an Ensemble of Unsupervised Similarity Measures](https://mlsanity.com/paper/2405.02095/) (2024)
- [Super Library Agent: Joint Generation and Maintenance of Multiple Applications Beyond the Single Codebase](https://mlsanity.com/paper/2608.29310/) (2026)
- [ExecRetrieval: Measuring the Functional-Correctness Gap in Code-Embedding Retrieval](https://mlsanity.com/paper/2609.01865/) (2026)

## 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.