Concise and consistent naming

By F. Deißenböck, M. Pizka. 2005

365 citations recorded by the source corpus.

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A Survey of Machine Learning for Big Code and Naturalness (2017, background): “drastically change the shape and frequency of its semantic units. Code has a higher neologism rate than text. Almost 70%of all charactersare identiﬁers and a developer must choose a name for each one [50]; when writing text, an author rarely names new things but usually choosesan existing word to us”
Modeling Vocabulary for Big Code Machine Learning (2019, background): “At 70% of source code [22], identifiers are the bulk source code and its vocabulary.”
An Empirical Investigation into Programming Language Syntax (2013, methodology): “In terms of programming language usability, a wide variety of topics have been studied, such as the use of identifiers [Deißenböck and Pizka 2005], method naming [Høst 2007; Høst and Østvold 2007], coding standards [Binkley et al.”
Learning to Spot and Refactor Inconsistent Method Names (2019, background): “Method names are the intuitive and vital information for developers to understand the behavior of programs or APIs [8]– Fig.”
Learning natural coding conventions (2014, background): “uages like Java and Python suggest speciﬁc coding styles [55, 64], while consortia publish guidelines for others, like C [8, 34]. High quality identiﬁer names lie at the heart of software engineering [6, 16, 20, 24, 42, 66, 69, 54]; they drive code readability and comprehension [12, 19, 20, 41, 44, ”