Ensuring Open Source Integrity: The Intersection of Copy-Based Reuse and License Compliance
- URL: http://arxiv.org/abs/2606.23495v1
- Date: Mon, 22 Jun 2026 15:44:06 GMT
- Title: Ensuring Open Source Integrity: The Intersection of Copy-Based Reuse and License Compliance
- Abstract summary: We create a copy-based code reuse network mapping direct copying across projects.<n>We find that code in repositories with permissive licenses, such as MIT and Apache, shows higher likelihood of reuse.<n>Public domain licenses, despite their aim of allowing unrestricted use, are associated with lower likelihood of copy-based reuse.
- Score: 11.111309839462814
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: As other creative work, source code is protected by copyright. The owner can license the work, e.g., to permit copy and other kinds of use, and even start legal proceeding against license violators. However, source code can be reused in subtle ways, e.g., via copying without explicit package manager dependencies, making it hard to reason about potential license noncompliance. Using the World of Code infrastructure approximating the entirety of open source software, in this paper we create a copy-based code reuse network mapping direct copying across projects, and use it to quantify the extent of potential license noncompliance across the entire open source ecosystem. In addition, we estimate regression models to understand whether code copying is affected by the origin project's license, and, if so, how it varies with other project characteristics. We find that code in repositories with permissive licenses, such as MIT and Apache, shows higher likelihood of reuse across programming languages. In contrast, copyleft licenses, like the GPL, exhibit mixed effects. Public domain licenses, despite their aim of allowing unrestricted use, are associated with lower likelihood of copy-based reuse. A widespread potential license noncompliance appears to accompany copy-based reuse, with 39.4% of project combinations at potential noncompliance risk, particularly when licenses are unclear or absent. Our findings reveal that only 2.43% of reuse detected through the copy-based network was discoverable via dependency analysis, highlighting the limitations of existing dependency-tracking tools in capturing copy-based reuse.
Related papers
- File-Level Copying Is an Implicit Dependency in Open Source [13.844153992502159]
Copying files across repositories removes four observable signals a package manager provides for a declared dependency.<n>From a 0.1% commit sample, we extract 690,500 copy events and retain 3,912 rationale-bearing copy commits for intent labeling.<n>We show that the 13 axial copy forms, spanning vendored dependencies, hardware/driver synchronization, scaffolding, UI assets, and direct source-code reuse, are unreliable proxies for developer intent.
arXiv Detail & Related papers (2026-07-02T11:37:59Z) - Anchored Decoding: Provably Reducing Copyright Risk for Any Language Model [99.16364381244445]
Modern language models (LMs) tend to memorize portions of their training data and emit verbatim spans.<n>We propose Anchored Decoding, a plug-and-play inference-time method for suppressing verbatim copying.<n>We evaluate our methods across six model pairs on long-form evaluations of copyright risk and utility.
arXiv Detail & Related papers (2026-02-06T19:00:14Z) - Copyright Detective: A Forensic System to Evidence LLMs Flickering Copyright Leakage Risks [123.36265437655187]
Copyright Detective is an interactive forensic system for detecting, analyzing, and visualizing potential copyright risks in LLM outputs.<n>It integrates multiple detection paradigms, including content recall testing, paraphrase-level similarity analysis, persuasive probing, and unlearning verification.
arXiv Detail & Related papers (2026-02-05T03:09:52Z) - How Do Semantically Equivalent Code Transformations Impact Membership Inference on LLMs for Code? [56.42119949944239]
We investigate whether semantically equivalent code transformation rules might be leveraged to evade MI detection.<n>We find that model accuracy drops by only 1.5% in the worst case for each rule.<n>Our results expose a critical loophole in license compliance enforcement for training large language models for code.
arXiv Detail & Related papers (2025-12-17T14:12:54Z) - Context-Guided Decompilation: A Step Towards Re-executability [50.71992919223209]
Binary decompilation plays an important role in software security analysis, reverse engineering and malware understanding.<n>Recent advances in large language models (LLMs) have enabled neural decompilation, but the generated code is typically only semantically plausible.<n>We propose ICL4Decomp, a hybrid decompilation framework that leverages in-context learning (ICL) to guide LLMs toward generating re-executable source code.
arXiv Detail & Related papers (2025-11-03T17:21:39Z) - Open Source at a Crossroads: The Future of Licensing Driven by Monetization [9.920603494655682]
Open Source Software Licenses (OSS licenses) ensure that software can be sold or distributed as part of aggregate programs from various sources without requiring a royalty or fee.<n>We argue that open source is at a crossroads, with a growing need to redefine its licensing models and support communities and critical software.
arXiv Detail & Related papers (2025-03-04T17:44:01Z) - Beyond Dependencies: The Role of Copy-Based Reuse in Open Source Software Development [5.412781090113212]
In Open Source Software, resources of any project are open for reuse by introducing dependencies or copying the resource itself.
Our aim is to enable future research and tool development to increase efficiency and reduce the risks of copy-based reuse.
arXiv Detail & Related papers (2024-09-07T13:50:40Z) - CopyBench: Measuring Literal and Non-Literal Reproduction of Copyright-Protected Text in Language Model Generation [132.00910067533982]
We introduce CopyBench, a benchmark designed to measure both literal and non-literal copying in LM generations.
We find that, although literal copying is relatively rare, two types of non-literal copying -- event copying and character copying -- occur even in models as small as 7B parameters.
arXiv Detail & Related papers (2024-07-09T17:58:18Z) - A Dataset and Benchmark for Copyright Infringement Unlearning from Text-to-Image Diffusion Models [52.49582606341111]
Copyright law confers creators the exclusive rights to reproduce, distribute, and monetize their creative works.
Recent progress in text-to-image generation has introduced formidable challenges to copyright enforcement.
We introduce a novel pipeline that harmonizes CLIP, ChatGPT, and diffusion models to curate a dataset.
arXiv Detail & Related papers (2024-01-04T11:14:01Z) - Dataset: Copy-based Reuse in Open Source Software [5.917654223291073]
In Open Source Software, the source code and any other resources available in a project can be viewed or reused by anyone subject to often permissive licensing restrictions.
This dataset seeks to encourage the studies of OSS-wide copy-based reuse by providing copying activity data that captures whole-file reuse in nearly all OSS.
arXiv Detail & Related papers (2023-12-14T22:08:09Z) - LiResolver: License Incompatibility Resolution for Open Source Software [13.28021004336228]
LiResolver is a fine-grained, scalable, and flexible tool to resolve license incompatibility issues for open source software.
Comprehensive experiments demonstrate the effectiveness of LiResolver, with 4.09% false positive (FP) rate and 0.02% false negative (FN) rate for incompatibility issue localization.
arXiv Detail & Related papers (2023-06-26T13:16:09Z) - Foundation Models and Fair Use [96.04664748698103]
In the U.S. and other countries, copyrighted content may be used to build foundation models without incurring liability due to the fair use doctrine.
In this work, we survey the potential risks of developing and deploying foundation models based on copyrighted content.
We discuss technical mitigations that can help foundation models stay in line with fair use.
arXiv Detail & Related papers (2023-03-28T03:58:40Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.