The popularity of the software repository site GitHub has created a rise in the Pull Based Development Models' use. An essential portion of pull-based development is the creation of Pull Requests. Pull Requests often have to be reviewed by an individual to be approved and accepted into the Master branch of a software repository. The reviewing process can often be time-consuming and introduce a relatively high level of lost development time. This paper examines thousands of pull requests to understand the most valuable metadata of pull requests. We then introduce metrics in comparing the metadata of pull requests to understand what makes an effective pull request. Breaking pull requests into specific metadata pieces and evaluating what each piece brings to the whole allows us to review pull requests more efficiently. A pull request is successful if and only if it merges with the Master Branch. The Master Branch is the main branch of the code repository and is the production codebase. Using data analysis tools, we can determine which parts of a pull request are critical in its merge time. The formation of a framework and creating a data structure to track and manage development resources in the Pull Based Development Model.
Computer Science and Engineering
Number of Pages
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License
Ellis, Canon, "Analysis of Github Pull Requests" (2020). Computer Science and Engineering Theses and Dissertations. 16.