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Who creates the most innovative open-source software projects? And what fate do these projects tend to have? Building on a long history of research to understand innovation in business and other domains, as well as recent advances towards modeling innovation in scientific research from the science of science field, in this paper we adopt the analogy of innovation as emerging from the novel recombination of existing bits of knowledge. As such, we consider as innovative the software projects that recombine existing software libraries in novel ways, i.e., those built on top of atypical combinations of packages as extracted from import statements. We then report on a large-scale quantitative study of innovation in the Python open-source software ecosystem. Our results show that higher levels of innovativeness are statistically associated with higher GitHub star counts, i.e., novelty begets popularity. At the same time, we find that controlling for project size, the more innovative projects tend to involve smaller teams of contributors, as well as be at higher risk of becoming abandoned in the long term. We conclude that innovation and open source sustainability are closely related and, to some extent, antagonistic.
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Ecosystem-level determinants of sustained activity in open-source projects: a case study of the PyPI ecosystem
Open-source projects do not exist in a vacuum. They benefit from reusing other projects and themselves are being reused by others, creating complex networks of interdependencies, i.e., software ecosystems. Therefore, the sustainability of projects comprising ecosystems may no longer by determined solely by factors internal to the project, but rather by the ecosystem context as well. In this paper we report on a mixed-methods study of ecosystem-level factors affecting the sustainability of open-source Python projects. Quantitatively, using historical data from 46,547 projects in the PyPI ecosystem, we modeled the chances of project development entering a period of dormancy (limited activity) as a function of the projects' position in their dependency networks, organizational support, and other factors. Qualitatively, we triangulated the revealed effects and further expanded on our models through interviews with project maintainers. Results show that the number of project ties and the relative position in the dependency network have significant impact on sustained project activity, with nuanced effects early in a project's life cycle and later on.
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- PAR ID:
- 10106647
- Date Published:
- Journal Name:
- Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering
- Page Range / eLocation ID:
- 644 to 655
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3236024.3236062
