Concept
We know that readability is a critical component of software quality, but the determining factors of readability are not well understood.
We can use data from human annotators obtained through SnippetSniper to extract local source code features (like line length) that are predicative of readability. Using that, we can construct an automated metric that can quickly "score" software on its readability in a way similar to Flesh-Kincaid in the natural language domain.
Papers
readability.pdf (ISSTA 2008)
readability_tse.pdf (TSE : submitted)
Presentations
Data Sets
Software
Readability Applet (source, required lib: weka)
External Software Resources
weka (API) - "a collection of machine learning algorithms for data mining tasks"
Find Bugs - Looks for errors in java byte code.