Understanding the Factors That Impact the Popularity of GitHub Repositories

By Hudson Silva Borges, André C. Hora, Marco Tulio de Oliveira Valente. IEEE International Conference on Software Maintenance and Evolution, 2016

346 citations recorded by the source corpus.

Software popularity is a valuable information to modern open source developers, who constantly want to know if their systems are attracting new users, if new releases are gaining acceptance, or if they are meeting user's expectations. In this paper, we describe a study on the popularity of software systems hosted at GitHub, which is the world's largest collection of open source software. GitHub provides an explicit way for users to manifest their satisfaction with a hosted repository: the stargazers button. In our study, we reveal the main factors that impact the number of stars of GitHub projects, including programming language and application domain. We also study the impact of new features on project popularity. Finally, we identify four main patterns of popularity growth, which are derived after clustering the time series representing the number of stars of 2,279 popular GitHub repositories. We hope our results provide valuable insights to developers and maintainers, which could help them on building and evolving systems in a competitive software market.

Subfields: Computer Science Applications, Information Systems, Information Systems and Management

View Paper: https://www.semanticscholar.org/paper/3ae5917f7c8875b380627053829f638be89aee88

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Science Applications

1. Hudson Silva Borges
2. Marco Tulio de Oliveira Valente

In Information Systems

1. Jan Vitek
2. Hudson Silva Borges
3. Pedro Martins
4. Marco Tulio de Oliveira Valente
5. Hitesh Sajnani
6. Di Yang
7. Petr Maj
8. Cristina Videira Lopes

In Information Systems and Management

1. Jan Vitek
2. Pedro Martins
3. Hitesh Sajnani
4. Di Yang
5. Petr Maj
6. Cristina Videira Lopes
7. Vaibhav Pratap Singh Saini
8. Jakub Zitny

Citations in the corpus

• DéjàVu: a map of code duplicates on GitHub (2017, background): “Consider for instance a subset that focuses on the most active projects, as done in [Borges et al. 2016], by filtering on the number of stars or commits a project has.”
• What's in a GitHub Star? Understanding Repository Starring Practices in a Social Coding Platform (2018, background): “Proposed Study: In a previous conference paper, we started an investigation on the factors and patterns that govern the number of stars of 2,500 GitHub projects [15].”