Modeling and recommending open source licenses with findOSSLicense

Abstract

Open source software is widely used in the software industry and the academia. Licenses applied to open source software provide the terms for its further use and distribution. Decisions regarding licensing for new software systems are essential for the system's future use. In this paper, we introduce findOSSLicense, a license recommender that guides users into choosing the appropriate open source license for their software under creation. We also introduce our license modeling concept that is used in the recommendation process. The license modeling captures the properties usually found in existing open source licenses following an analysis performed on license texts. The recommendation process of findOSSLicense is based on a hybrid recommender that uses constraint-based, content-based and collaborative filtering giving also space for flexibility in the use of the system by its end-users who can adapt some system properties. User input, but also external sources of information including existing open source projects, are considered for the creation of the recommendations, whereas licenses used in third party software employed in the software are examined on a limited basis. findOSSLicense has been evaluated with the participation of users of various expertise.