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

Simmons, Andrew, Barnett, Scott, Rivera Villicana, Jessica, Bajaj, A and Vasa, Venkata Rajesh 2020, A large-scale comparative analysis of Coding Standard conformance in Open-Source Data Science projects, in ESEM '20: Proceedings of the 14th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement, ACM, New York, N.Y., pp. 1-11, doi: 10.1145/3382494.3410680.

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Title A large-scale comparative analysis of Coding Standard conformance in Open-Source Data Science projects
Author(s) Simmons, AndrewORCID iD for Simmons, Andrew orcid.org/0000-0001-8402-2853
Barnett, ScottORCID iD for Barnett, Scott orcid.org/0000-0002-3187-4937
Rivera Villicana, Jessica
Bajaj, AORCID iD for Bajaj, A orcid.org/0000-0003-4805-1467
Vasa, Venkata Rajesh
Conference name Empirical Software Engineering and Measurement. Conference (2020 : Bari, Italy)
Conference location Bari, Italy
Conference dates 2020/10/05 - 2020/10/09
Title of proceedings ESEM '20: Proceedings of the 14th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement
Publication date 2020
Start page 1
End page 11
Total pages 11
Publisher ACM
Place of publication New York, N.Y.
Keyword(s) Open-source software
data science
machine learning
code style
code smells
code quality
code conventions
ISBN 9781450375801
ISSN 1949-3770
1949-3789
Language eng
DOI 10.1145/3382494.3410680
HERDC Research category E1 Full written paper - refereed
Persistent URL http://hdl.handle.net/10536/DRO/DU:30145424

Document type: Conference Paper
Collection: A2I2 (Applied Artificial Intelligence Institute)
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