Author entropy vs. file size in the gnome suite of applications

Authors:
Jason R. Casebolt;Jonathan L. Krein;Alexander C. MacLean;Charles D. Knutson;Daniel P. Delorey
Affiliations:
SEQuOIA Lab, Brigham Young University, USA;SEQuOIA Lab, Brigham Young University, USA;SEQuOIA Lab, Brigham Young University, USA;SEQuOIA Lab, Brigham Young University, USA;Google, Inc., USA
Venue:
MSR '09 Proceedings of the 2009 6th IEEE International Working Conference on Mining Software Repositories
Year:
2009

Citing 0
Cited 2

Interactive churn metrics: socio-technical variants of code churn

ACM SIGSOFT Software Engineering Notes
A historical dataset for the gnome ecosystem

Proceedings of the 10th Working Conference on Mining Software Repositories

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present the results of a study in which author entropy was used to characterize author contributions per file. Our analysis reveals three patterns: banding in the data, uneven distribution of data across bands, and file size dependent distributions within bands. Our results suggest that when two authors contribute to a file, large files are more likely to have a dominant author than smaller files.