Detecting and Fixing Violations of Modification Terms in Open Source Licenses during Forking

Kuo‐Cheng Huang, Xiaodong Yu,Bihuan Chen, Zi-Li Zhou, Jing Guo,Xin Peng

arXiv (Cornell University)(2023)

引用 0|浏览5
暂无评分
摘要
Open source software brings benefit to software community, but also introduces legal risks caused by license violations, which result in serious consequences such as lawsuits and financial losses. To mitigate legal risks, some approaches have been proposed to identify licenses, detect license incompatibilities and inconsistencies, and recommend licenses. As far as we know, however, there is no prior work to understand modification terms in open source licenses or to detect and fix violations of modification terms. To bridge this gap, we first empirically characterize modification terms in 47 open source licenses. These licenses all require certain forms of "notice" to describe the modifications made to the original work. Inspired by our study, we then design LiVo to automatically detect and fix violations of modification terms in open source licenses during forking. Our evaluation has shown the effectiveness and efficiency of LiVo. 18 pull requests of fixing modification term violations have received positive responses. 8 have been merged.
更多
查看译文
关键词
modification terms,fixing violations,forking,licenses,open source
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要