How R Developers explain their Package Choice: A Survey

Addi Malviya-Thakur, Audris Mockus, Russell Zaretzki, Bogdan Bichescu, Randy Bradley

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Background: Contemporary software development relies heavily on reusing already implemented functionality, usually in the form of packages. Aims: We aim to shed light on developers' preferences when selecting packages in R language. Method: To do that, we create and administer a survey to over 1000 developers who have added one of two common dataframe enhancement libraries in R to their projects: data.table or tidyr. We design a questionnaire using the Social Contagion Theory (SCT) following prior work on technology adoption and ensure that key dimensions affecting developer choice are considered. Results: Of the 1085 developers we contacted, 803 completed the survey asking them to prioritize various factors known to affect developer perceptions of package quality and to provide their background. Most developers self-identified as data scientists with two to five years of work experience. We found significant differences between the preferences of developers who chose data.table and tidyr. Surprisingly, package reputation based on easy-to-see measures, such as the number of stars on GitHub, was not an important factor for either group. Conclusions: Our findings demonstrate the inherently social nature of package adoption. They can help design future studies on how different populations of developers make decisions on which software packages to use in their projects. Finally, package developers and maintainers can benefit by better understanding the prime concerns of the users of their packages.

Original languageEnglish
Title of host publication2023 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2023
PublisherIEEE Computer Society
ISBN (Electronic)9781665452236
DOIs
StatePublished - 2023
Event17th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2023 - New Orleans, United States
Duration: Oct 26 2023Oct 27 2023

Publication series

NameInternational Symposium on Empirical Software Engineering and Measurement
ISSN (Print)1949-3770
ISSN (Electronic)1949-3789

Conference

Conference17th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2023
Country/TerritoryUnited States
CityNew Orleans
Period10/26/2310/27/23

Keywords

  • Code reuse
  • Empirical Software engineering
  • R System
  • Social aspects
  • Social Contagion Theory
  • Software engineering research
  • Software measurement
  • Software Supply chains
  • User behavior

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