Evaluating Unit Testing Practices in R Packages.
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| Title: | Evaluating Unit Testing Practices in R Packages. |
|---|---|
| Authors: | Vidoni, Melina1 melina.vidoni@rmit.edu.au |
| Source: | ICSE: International Conference on Software Engineering. 5/22/2021, p1523-1534. 12p. |
| Subjects: | Computer software packaging, Learning curve, Artificial intelligence, Computer software development, Software engineering |
| Abstract: | Testing Technical Debt (TTD) occurs due to shortcuts (non-optimal decisions) taken about testing; it is the test dimension of technical debt. R is a package-based programming ecosystem that provides an easy way to install third-party code, datasets, tests, documentation and examples. This structure makes it especially vulnerable to TTD because errors present in a package can transitively affect all packages and scripts that depend on it. Thus, TTD can effectively become a threat to the validity of all analysis written in R that rely on potentially faulty code. This two-part study provides the first analysis in this area. First, 177 systematically-selected, open-source R packages were mined and analysed to address quality of testing, testing goals, and identify potential TTD sources. Second, a survey addressed how R package developers perceive testing and face its challenges (response rate of 19.4%). Results show that testing in R packages is of low quality; the most common smells are inadequate and obscure unit testing, improper asserts, inexperienced testers and improper test design. Furthermore, skilled R developers still face challenges such as time constraints, emphasis on development rather than testing, poor tool documentation and a steep learning curve. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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