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  • 标题:checkmate: Fast Argument Checks for Defensive R Programming
  • 本地全文:下载
  • 作者:Michel Lang
  • 期刊名称:R News
  • 印刷版ISSN:1609-3631
  • 出版年度:2017
  • 卷号:9
  • 期号:1
  • 页码:437-445
  • 语种:English
  • 出版社:The R Foundation for Statistical Computing
  • 摘要:Dynamically typed programming languages like R allow programmers to write generic, flexible and concise code and to interact with the language using an interactive Read-eval-print-loop (REPL). However, this flexibility has its price: As the R interpreter has no information about the expected variable type, many base functions automatically convert the input instead of raising an exception. Unfortunately, this frequently leads to runtime errors deeper down the call stack which obfuscates the original problem and renders debugging challenging. Even worse, unwanted conver sions can remain undetected and skew or invalidate the results of a statistical analysis. As a resort, assertions can be employed to detect unexpected input during runtime and to signal understandable and traceable errors. The package checkmate provides a plethora of functions to check the type and related properties of the most frequently used R objects and variable types. The package is mostly written in C to avoid any unnecessary performance overhead. Thus, the programmer can conveniently write concise, well-tested assertions which outperforms custom R code for many applications. Fur thermore, checkmate simplifies writing unit tests using the framework testthat (Wickham, 2011) by extending it with plenty of additional expectation functions, and registered C routines are available for package developers to perform assertions on arbitrary SEXPs (internal data structure for R objects implemented as struct in C) in compiled code.
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