Quantifying the Hidden Costs of Open-Source License Selection
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Abstract
This study fills a gap in the existing literature regarding OSS licensing and maintenance by evaluating empirically if some OSS license types (permissive, weak or strong copyleft) create a different level of maintenance efficiencies. In order to achieve this goal, researchers created a data set of 60 OSS repositories using six types of licenses and gathered from a 120-day window of activity via the GitHub REST API. The results of the study suggest that each of the three license types has a significant influence upon both the level of community participation and the quantity of issues created in each specific repository. That being said, the findings suggest that permissive licenses (e.g., MIT and Apache 2.0), will have a greater number of people contributing to them (thus, higher levels of community participation), but at the same time will require a higher degree of administrative effort by the maintainer of the repository than will either of the other types of licenses, whereas repositories that are licensed under copylefts generally will have less contribution to their repositories (therefore, lower community participation), but will allow maintainers to more effectively control and manage the maintenance of their respective repositories due to a greater degree of stability.One of the most significant results in our study shows that the time taken to resolve issues is not affected by the license's restrictions. Instead, we found that the speed with which issues can be resolved is dependent upon the inner workings of managing projects, and not dependent upon the user's license. In fact, this evidence shows that selection of a project license will affect the amount of maintenance work created on the project, as well as the structure of the overall project; and therefore, is not only a legal decision but also a strategic operational decision. © 2026 IEEE.
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Software Licensing, Open Source Software, Maintainability, Mining Software Repositories, Software Metrics
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717
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722
