Wednesday 12 March 2025
The study of large language models (LLMs) has led to significant advancements in software development, but a crucial aspect of their functionality remains understudied: the provenance of generated code. Provenance refers to the origin and history of a piece of code, including its licensing, ownership, and any intellectual property rights associated with it.
Researchers have long been concerned about the potential legal implications of LLMs generating code that may infringe on existing copyrights or licenses. The issue is particularly relevant in the context of open-source software development, where developers rely on others’ work to create their own projects.
A recent study published in a prominent academic journal investigated the extent to which LLM-based assistants provide links to the original sources of generated code snippets. Bing CoPilot and Google Gemini, two popular LLM-based code generation tools, were analyzed for their ability to provide relevant links to the original authors or licenses of the generated code.
The results were mixed. While both assistants provided a significant number of links, many of them were irrelevant or failed to accurately attribute the original source of the code. The study found that 66% of the links from Bing CoPilot and 28% from Google Gemini were relevant, meaning they pointed to the correct origin of the generated code.
The implications of these findings are significant. LLMs may be generating code that is not properly licensed or attributed, potentially leading to legal disputes and intellectual property issues. Furthermore, the lack of transparency surrounding the provenance of generated code raises concerns about the accountability of developers who use these tools in their projects.
The study highlights the need for better tools and methodologies to ensure the integrity and accountability of LLM-generated code. Developers must be able to accurately track the origin and history of code snippets used in their projects, ensuring that they are properly licensed and attributed.
In addition to technical solutions, the study also underscores the importance of ethical considerations in software development. As LLMs become increasingly prevalent in the industry, developers must prioritize transparency, accountability, and responsible use of these powerful tools.
The findings of this study serve as a wake-up call for the software development community, emphasizing the need for greater attention to the provenance of generated code. By addressing this critical issue, developers can ensure that their projects are built on a foundation of integrity, trust, and respect for intellectual property rights.
Cite this article: “Provenance in Code Generation: The Unstudied Aspect of Large Language Models”, The Science Archive, 2025.
Large Language Models, Code Generation, Provenance, Intellectual Property, Open-Source Software, Copyrights, Licensing, Accountability, Transparency, Ethics
