Is There a Correlation Between Readme Content and Project Meta‐Characteristics?

Abstract

ContextDevelopers often turn to readme files in GitHub repositories when they intend to contribute, reuse, or extend a project. These files act as a primary source of information, offering insights into various aspects of the repository. The content and organization of readme can have a significant impact on the project's popularity, its development progress, and the growth of its community.ObjectiveWe examine the growth of GitHub repositories through the lens of their meta‐characteristics, which encompass factors like popularity, community engagement, and development progress, to study the relationship of readme files with repository growth. To achieve this, we conduct a correlation analysis to assess the relationship between project meta‐characteristics and the content and organization of a readme file.MethodsTo conduct a correlation analysis between readme files and project meta‐characteristics, we compiled a data set of readme files from 2000 public GitHub repositories, encompassing 10 primary programming languages. We define metrics for popularity, progress, and community engagement meta‐characteristics and analyze the correlation of structural features and categorical content in readme files against these metrics using non‐parametric statistical tests.ResultsThe results are presented from three distinct perspectives of project meta‐characteristics across 10 programming languages. The results reveal a positive and strong association of external reference links, contribution guidelines, and team details in readme files with better popularity and larger community size. However, the influence of contribution guidelines in readme files on rate of progress is not clearly evident.ConclusionThe study was conducted to assess the correlation of readme file content on repository popularity, development progress, and community size. Our experiments revealed positive correlations between readme content and project meta‐characteristics. However, the extent of correlation varied between repositories across programming languages and meta‐characteristics. We discussed the implications of our findings for developers and researchers and have proposed recommendations for repository owners to organize readme files toward increasing the growth of the repositories with better meta‐characteristics.