%0 Conference Paper %B 2009 6th IEEE International Working Conference on Mining Software Repositories (MSR)2009 6th IEEE International Working Conference on Mining Software Repositories %D 2009 %T Author entropy vs. file size in the GNOME suite of applications %A Casebolt, Jason R. %A Krein, Jonathan L. %A MacLean, Alexander C. %A Knutson, Charles D. %A Delorey, Daniel P. %K author entropy %K contributions %K gnome %K msr challenge %X 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. %B 2009 6th IEEE International Working Conference on Mining Software Repositories (MSR)2009 6th IEEE International Working Conference on Mining Software Repositories %I IEEE %C Vancouver, BC, Canada %P 91 - 94 %@ 978-1-4244-3493-0 %R 10.1109/MSR.2009.5069484 %0 Conference Paper %B 4th Workshop on Public Data about Software Development (WoPDaSD 2009) %D 2009 %T Language entropy: A metric for characterization of author programming language distribution %A Krein, Jonathan L. %A MacLean, Alexander C. %A Delorey, Daniel P. %A Knutson, Charles D. %A Eggett, Dennis L. %K contributions %K developers %K language entropy %K lines of code %K loc %K multiple languages %K programming languages %K sourceforge %X Programmers are often required to develop in multiple languages. In an effort to study the effects of programming language fragmentation on productivity—and ultimately on a programmer’s problem solving abilities—we propose a metric, language entropy, for characterizing the distribution of an individual’s development efforts across multiple programming languages. To evaluate this metric, we present an observational study examining all project contributions (through August 2006) of a random sample of 500 SourceForge developers. Using a random coefficients model, we found a statistically significant correlation (alpha level of 0.05) between language entropy and the size of monthly pro ject contributions (measured in lines of code added). Our results indicate that language entropy is a good candidate for characterizing author programing language distribution. %B 4th Workshop on Public Data about Software Development (WoPDaSD 2009) %8 2009 %> https://flosshub.org/sites/flosshub.org/files/LanguageEntropy-JonathanKrein.pdf