- “OSS Review Toolkit: A Framework for Automated Analysis of Open Source Software Licenses” by Harshitha Ramesh, Kavitha Jaganathan, and Krishnaprasad Thirunarayan (2019)
This paper describes the OSS Review Toolkit, a framework that automates the analysis of open source software licenses. The toolkit uses natural language processing techniques to extract license information from source code and documentation, and then maps this information to known license templates. The authors demonstrate the effectiveness of the toolkit through experiments on several open source projects.
- “OSS Review Toolkit: Supporting License Compliance in Large-Scale Open Source Projects” by Sina Shahbazmohamadi, Andreas Schreiber, and Dirk Riehle (2020)
This paper presents an extended version of the OSS Review Toolkit that supports license compliance in large-scale open source projects. The authors describe how they integrated the toolkit into their development process and used it to identify licensing issues in over 100 open source projects. They also discuss the challenges involved in scaling up license compliance efforts across multiple teams and repositories.
- “Automated License Compliance Checking Using OSS Review Toolkit” by Shubham Kumar Jain and Chetan Arora (2021)
This paper describes how the OSS Review Toolkit can be used to automate license compliance checking in software development workflows. The authors provide a step-by-step guide for integrating the toolkit into a continuous integration/continuous deployment pipeline, and demonstrate its effectiveness through experiments on several open source projects. They also discuss potential limitations of the approach and suggest future research directions.
- “Improving Open Source License Compliance with Machine Learning Techniques” by Harshitha Ramesh, Kavitha Jaganathan, Krishnaprasad Thirunarayan, Peter Dolog, and Martin Staudt (2021)
This paper explores how machine learning techniques can be used to improve the accuracy and efficiency of license compliance analysis using the OSS Review Toolkit. The authors propose a novel approach that combines natural language processing with machine learning models to automatically classify licenses based on their text content. They demonstrate the effectiveness of this approach through experiments on several open source projects, and discuss potential applications in industry settings.
