Language Entropy: A Metric for Characterization of Author Programming Language Distribution

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 project contributions (measured in lines of code added). Our results indicate that language entropy is a good candidate for characterizing author programing language distribution.