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. R’s package 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, R packages’ 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 does not have good quality; the most common smells are inadequate and obscure unit testing, improper asserts, inexperienced testes and improper test design. Furthermore, skilled developers still face challenges such as time constraints, emphasis on development rather than testing, poor tool documentation and a steep learning curve.