@conference {1204,
	title = {Language entropy: A metric for characterization of author programming language distribution},
	booktitle = {4th Workshop on Public Data about Software Development (WoPDaSD 2009)},
	year = {2009},
	note = {The data set used in this study was previously collected for a separate, but related work. It was originally extracted from the SourceForge Research Archive (SFRA), August 2006. For a detailed discussion of the data source, collection tools and processes, and summary statistics, see [6]."

"From the initial data set we extracted a random sample of 500 developers3 along with descriptive details of all revisions that those developers made since the inception of the projects on which they worked. We then condensed this sample by totaling the lines of code added by each developer for each month in which that developer made at least one code submission."
[6] Daniel P. Delorey, Charles D. Knutson, and Alex MacLean. Studying production phase sourceforge projects: A case study using cvs2mysql and sfra+. In Second International Workshop on Public Data about Software Development (WoPDaSD {\textquoteright}07), June 2007.},
	month = {2009},
	abstract = {Programmers are often required to develop in multiple languages. In an effort to study the effects of programming language fragmentation on productivity{\textemdash}and ultimately on a programmer{\textquoteright}s problem solving abilities{\textemdash}we propose a metric, language entropy, for characterizing the distribution of an individual{\textquoteright}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.},
	keywords = {contributions, developers, language entropy, lines of code, loc, multiple languages, programming languages, sourceforge},
	attachments = {https://flosshub.org/sites/flosshub.org/files/LanguageEntropy-JonathanKrein.pdf},
	author = {Krein, Jonathan L. and MacLean, Alexander C. and Delorey, Daniel P. and Knutson, Charles D. and Eggett, Dennis L.}
}
@conference {940,
	title = {Using Latent Dirichlet Allocation for automatic categorization of software},
	booktitle = {2009 6th IEEE International Working Conference on Mining Software Repositories (MSR)2009 6th IEEE International Working Conference on Mining Software Repositories},
	year = {2009},
	pages = {163 - 166},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Vancouver, BC, Canada},
	abstract = {In this paper, we propose a technique called LACT for automatically categorizing software systems in open-source repositories. LACT is based on latent Dirichlet Allocation, an information retrieval method which is used to index and analyze source code documents as mixtures of probabilistic topics. For an initial evaluation, we performed two studies. In the first study, LACT was compared against an existing tool, MUDABlue, for classifying 41 software systems written in C into problem domain categories. The results indicate that LACT can automatically produce meaningful category names and yield classification results comparable to MUDABlue. In the second study, we applied LACT to 43 software systems written in different programming languages such as C/C++, Java, C$\#$, PHP, and Perl. The results indicate that LACT can be used effectively for the automatic categorization of software systems regardless of the underlying programming language or paradigm. Moreover, both studies indicate that LACT can identify several new categories that are based on libraries, architectures, or programming languages, which is a promising improvement as compared to manual categorization and existing techniques.},
	keywords = {categorization, category mining, lact, mudablue, multiple languages, repository},
	isbn = {978-1-4244-3493-0},
	doi = {10.1109/MSR.2009.5069496},
	attachments = {https://flosshub.org/sites/flosshub.org/files/163MSR2009_TianPos.pdf},
	author = {Tian, Kai and Revelle, Meghan and Poshyvanyk, Denys}
}
