Do People Use Naming Conventions in SQL Programming?

Papamichail, Aggelos; Zarras, Apostolos; Vassiliadis, Panos

doi:10.1007/978-3-030-38919-2_35

Cited by 4 publications

(1 citation statement)

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“…Recent studies have focused on conformance of coding standards applied to application categories [4,21,32] and has not considered the inherent technical domain [5] of Data Science. For example, Data Science applications may follow implicit or undocumented guidelines for 1) describing mathematical notation when implementing algorithms , e.g.…”

Section: Introductionmentioning

confidence: 99%

A large-scale comparative analysis of Coding Standard conformance in Open-Source Data Science projects

Simmons

Barnett

Rivera-Villicana

et al. 2020

Proceedings of the 14th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)

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Background: Meeting the growing industry demand for Data Science requires cross-disciplinary teams that can translate machine learning research into production-ready code. Software engineering teams value adherence to coding standards as an indication of code readability, maintainability, and developer expertise. However, there are no large-scale empirical studies of coding standards focused specifically on Data Science projects. Aims: This study investigates the extent to which Data Science projects follow code standards. In particular, which standards are followed, which are ignored, and how does this differ to traditional software projects? Method: We compare a corpus of 1048 Open-Source Data Science projects to a reference group of 1099 non-Data Science projects with a similar level of quality and maturity. Results: Data Science projects suffer from a significantly higher rate of functions that use an excessive numbers of parameters and local variables. Data Science projects also follow different variable naming conventions to non-Data Science projects. Conclusions: The differences indicate that Data Science codebases are distinct from traditional software codebases and do not follow traditional software engineering conventions. Our conjecture is that this may be because traditional software engineering conventions are inappropriate in the context of Data Science projects. CCS CONCEPTS• Software and its engineering → Software libraries and repositories.

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Section: Introductionmentioning

confidence: 99%