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arXiv · 2304.04265

Dependently Typing R Vectors, Arrays, and Matrices

John Wrenn·Anjali Pal·Alexa VanHattum·Shriram Krishnamurthi
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Abstract

The R programming language is widely used in large-scale data analyses. It contains especially rich built-in support for dealing with vectors, arrays, and matrices. These operations feature prominently in the applications that form R's raison d'\^etre, making their behavior worth understanding. Furthermore, ostensibly for programmer convenience, their behavior in R is a notable extension over the corresponding operations in mathematics, thereby offering some challenges for specification and static verification. We report on progress towards statically typing this aspect of the R language. The interesting aspects of typing, in this case, warn programmers about violating bounds, so the types must necessarily be dependent. We explain the ways in which R extends standard mathematical behavior. We then show how R's behavior can be specified in LiquidHaskell, a dependently-typed extension to Haskell. In the general case, actually verifying library and client code is currently beyond LiquidHaskell's reach; therefore, this work provides challenges and opportunities both for typing R and for progress in dependently-typed programming languages.

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John Wrenn, Anjali Pal, Alexa VanHattum, Shriram Krishnamurthi. 2023-04-09. Dependently Typing R Vectors, Arrays, and Matrices. https://arxiv.org/abs/2304.04265

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