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 language | English |
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| Title of host publication | 2023 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2023 |
| Publisher | IEEE Computer Society |
| ISBN (Electronic) | 9781665452236 |
| DOIs | |
| State | Published - 2023 |
| Event | 17th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2023 - New Orleans, United States Duration: Oct 26 2023 → Oct 27 2023 |
Publication series
| Name | International Symposium on Empirical Software Engineering and Measurement |
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| ISSN (Print) | 1949-3770 |
| ISSN (Electronic) | 1949-3789 |
Conference
| Conference | 17th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2023 |
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| Country/Territory | United States |
| City | New Orleans |
| Period | 10/26/23 → 10/27/23 |
Funding
This manuscript has been authored by UT-Battelle, LLC, USA under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a non-exclusive, paid up, irrevocable, worldwide license to publish or reproduce the published form of the manuscript, or allow others to do so, for U.S. Government purposes. The DOE will provide public access to these results in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). This work was supported by NSF awards 1633437, 1901102, and 2120429.
Keywords
- Code reuse
- Empirical Software engineering
- R System
- Social Contagion Theory
- Social aspects
- Software Supply chains
- Software engineering research
- Software measurement
- User behavior