Designing Types for R, Empirically (Dataset)

<p>This dataset is intended to accompany the paper &quot;Designing Types for R, Empirically&quot; (@ OOPSLA&#39;20,&nbsp;<a href="https://2020.splashcon.org/details/splash-2020-oopsla/57/Designing-Types-for-R-Empirically">link to paper</a>). This data was obtained by running the Typetracer (aka propagatr) dynamic analysis tool (<a href="https://github.com/PRL-PRG/propagatr">link to tool</a>) on the test, example, and vignette code of a corpus of &gt;400 extensively used R packages.<br> <br> Specifically, this dataset contains:</p> <ol> <li>function type traces for &gt;400 R packages (raw-traces.tar.gz);</li> <li>trace data processed into a more readable/usable form (processed-traces.tar.gz), which was used in obtaining results in the paper;</li> <li>inferred type declarations for the &gt;400 R packages using various strategies to merge the processed traces (see type-declarations-* directories),&nbsp;and finally;</li> <li>contract assertion data from running the reverse dependencies of these packages and checking function usage against the declared types (contract-assertion-reverse-dependencies.tar.gz).</li> </ol> <p>&nbsp;A preprint of the paper is also included, which summarizes our findings.</p> <p><strong>Fair warning Re: data size:</strong>&nbsp;the raw traces, once uncompressed, take up nearly 600GB. The already processed traces are in the 10s of GB, which should be more manageable for a consumer-grade computer.</p>