Linguistic Relativity and Programming Languages
Jiahao Chen
TL;DR
This paper explores how programming languages influence coding patterns and abstractions, drawing parallels to linguistic relativity, and examines how Julia enables diverse expression through its flexible design.
Contribution
It introduces the concept of linguistic relativity in programming languages and analyzes how language design affects coding practices and user expression.
Findings
Differences in language syntax reflect linguistic relativity.
Julia's flexibility supports diverse programming abstractions.
Language choice impacts coding patterns and user expression.
Abstract
The use of programming languages can wax and wane across the decades. We examine the split-apply- combine pattern that is common in statistical computing, and consider how its invocation or implementation in languages like MATLAB and APL differ from R/dplyr. The differences in spelling illustrate how the concept of linguistic relativity applies to programming languages in ways that are analogous to human languages. Finally, we discuss how Julia, by being a high performance yet general purpose dynamic language, allows its users to express different abstractions to suit individual preferences.
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Taxonomy
TopicsSensory Analysis and Statistical Methods · Data Mining Algorithms and Applications · Evolutionary Algorithms and Applications