Machine learning model for identification of frontend and backend repositories in Github

Frontend and Backend repositories are the main components of the multi-repository structure. The developers or team managers upfront mostly do the identification of these repositories, but in Github, there is almost no tool or third party identification to identify these repositories. Since Github is the largest open source platform and is used by, many researchers and identification of these two repositories are crucial. This paper shows how this problem can be solved by building a machine learning model based on the file structure of the repository. The model has proven to be very successful with an accuracy of over 90% and can be used not only to identify the repository type, but also to identify the development language and environment.