Studying the Difference Between Natural and Programming Language Corpora
June 06, 2018 ยท Declared Dead ยท ๐ Empirical Software Engineering
"No code URL or promise found in abstract"
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Authors
Casey Casalnuovo, Kenji Sagae, Prem Devanbu
arXiv ID
1806.02437
Category
cs.CL: Computation & Language
Citations
38
Venue
Empirical Software Engineering
Last Checked
4 months ago
Abstract
Code corpora, as observed in large software systems, are now known to be far more repetitive and predictable than natural language corpora. But why? Does the difference simply arise from the syntactic limitations of programming languages? Or does it arise from the differences in authoring decisions made by the writers of these natural and programming language texts? We conjecture that the differences are not entirely due to syntax, but also from the fact that reading and writing code is un-natural for humans, and requires substantial mental effort; so, people prefer to write code in ways that are familiar to both reader and writer. To support this argument, we present results from two sets of studies: 1) a first set aimed at attenuating the effects of syntax, and 2) a second, aimed at measuring repetitiveness of text written in other settings (e.g. second language, technical/specialized jargon), which are also effortful to write. We find find that this repetition in source code is not entirely the result of grammar constraints, and thus some repetition must result from human choice. While the evidence we find of similar repetitive behavior in technical and learner corpora does not conclusively show that such language is used by humans to mitigate difficulty, it is consistent with that theory.
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