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An empirical comparison of dependency network evolution in seven software packaging ecosystems

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Abstract

Nearly every popular programming language comes with one or more package managers. The software packages distributed by such package managers form large software ecosystems. These packaging ecosystems contain a large number of package releases that are updated regularly and that have many dependencies to other package releases. While packaging ecosystems are extremely useful for their respective communities of developers, they face challenges related to their scale, complexity, and rate of evolution. Typical problems are backward incompatible package updates, and the risk of (transitively) depending on packages that have become obsolete or inactive. This manuscript uses the libraries.io dataset to carry out a quantitative empirical analysis of the similarities and differences between the evolution of package dependency networks for seven packaging ecosystems of varying sizes and ages: Cargo for Rust, CPAN for Perl, CRAN for R, npm for JavaScript, NuGet for the .NET platform, Packagist for PHP, and RubyGems for Ruby. We propose novel metrics to capture the growth, changeability, reusability and fragility of these dependency networks, and use these metrics to analyze and compare their evolution. We observe that the dependency networks tend to grow over time, both in size and in number of package updates, while a minority of packages are responsible for most of the package updates. The majority of packages depend on other packages, but only a small proportion of packages accounts for most of the reverse dependencies. We observe a high proportion of “fragile” packages due to a high and increasing number of transitive dependencies. These findings are instrumental for assessing the quality of a package dependency network, and improving it through dependency management tools and imposed policies.

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Notes

  1. Creative Commons Attribution-ShareAlike 4.0 International, see https://creativecommons.org/licenses/by-sa/4.0/.

  2. https://github.com/ecos-umons/extractoR

  3. R2 ? [0, 1] and the closer to 1 the better the model fits the data.

  4. CPAN is twice as old as the other considered ecosystems except for CRAN.

  5. Because the choice of one month period may seem arbitrary, we also computed this indexfor several other periods, and did not observe different behaviors.

  6. http://grimoirelab.github.io

  7. https://bitergia.com

  8. https://github.com/ecos-umons/extractoR

  9. https://chaoss.community

  10. https://www.secohealth.org (October 2017 - September 2019

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Acknowledgements

This research was carried out in the context of FRQ-FNRS collaborative research project R.60.04.18.F “SECOHealth”, ARC research project AUWB-12/17-UMONS-3 “Ecological Studies of Open Source Software Ecosystems”, and FNRS Research Credit J.0023.16 “Analysis of Software Project Survival”. We express our gratitude to Andrew Nesbitt and Ben Nickolls, both from libaries.io and dependencyci.com, for making the package manager dependency data available, and for the very useful email discussions. We thank Jesus Gonzalez-Barahona and Daniel Izquierdo from Bitergia for their relevant feedback. We thank Eleni Constantinou, Alexander Serebrenik and Damian Tamburri for proofreading this work.

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  1. COMPLEXYS Research Institute, University of Mons, Mons, Belgium

    Alexandre Decan, Tom Mens & Philippe Grosjean

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  1. Alexandre Decan
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Correspondence to Alexandre Decan.

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Communicated by: Gabriele Bavota and Andrian Marcus

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Decan, A., Mens, T. & Grosjean, P. An empirical comparison of dependency network evolution in seven software packaging ecosystems. Empir Software Eng 24, 381–416 (2019). https://doi.org/10.1007/s10664-017-9589-y

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