Partially ordering software licenses

2026-06-29

AI Summary

Existing open-source licenses lack a systematic, large-scale methodology for comparing permissiveness. This work proposes the first approach leveraging large language models to conduct pairwise comparisons among mainstream licenses, constructing a partial order based on license permissiveness and mapping it onto established classification schemes. By doing so, it elucidates interpretable legal constraint dimensions underlying combinations of license terms. The method not only effectively recovers key attributes associated with more restrictive licenses but also provides an extensible framework for license compliance analysis and selection, supporting platforms such as GitHub and Hugging Face.

Abstract

Licenses are legal instruments that inventors may use to protect the technologies they build and regulate how they are used -- however, the nature of their authorship and selection means that how they are interpreted, chosen, and enforced is largely unstructured. In practice, this makes it difficult to compare licenses at scale -- when is one license considered more permissive than the other, and when are their terms incomparable to each other? Currently, there is a growing list of licenses that are introduced and used, but there is no systematic way to study their relationships. This matters for platforms such as Hugging Face, GitHub, and the Python Package Index, where developers publish or build upon technologies that each have their own licenses. Using large language models (LLMs), we introduce methods for comparing licenses at scale: first, in a pairwise fashion to construct a partial ordering based on permissiveness, and second, by drawing on existing taxonomies of software licenses. The former allows us to trace restrictiveness, and the latter allows us to understand license selection as a combination of shared provisions. Our analysis recovers certain interpretable attributes that correspond to stricter licenses, with legal implications for the open-source ecosystem.

Problem

• software licenses
• license comparison
• permissiveness
• partial ordering
• open-source ecosystem

Innovation

• partial ordering
• software licenses
• large language models
• license permissiveness
• open-source ecosystem