code::proof: Prepare for most weather conditions

10/14/2019
by   Charles T. Gray, et al.
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Computational tools for data analysis are being released daily on repositories such as the Comprehensive R Archive Network. How we integrate these tools to solve a problem in research is increasingly complex and requiring frequent updates. To mitigate these Kafkaesque computational challenges in research, this manuscript proposes toolchain walkthrough, an opinionated documentation of a scientific workflow. As a practical complement to our proof-based argument (Gray and Marwick, arXiv, 2019) for reproducible data analysis, here we focus on the practicality of setting up a reproducible research compendia, with unit tests, as a measure of code::proof, confidence in computational algorithms.

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