Every software system has a history. We find traces of a system's history in software repositories, which are used by developers when building and maintaining their systems. Each repository tells us a part of the history, from its perspective: Issue repositories murmur dark events involving defective and flawed entities; versioning system repositories narrate about restless artifacts and classes that nobody would ever touch; mailing list archives report of unexpected stories on developers’ interactions and opinions.

But... can we seriously trust these repositories? Can we just listen to what they tell us and behave accordingly? Many wise researchers warmly warned us about the risks of showing such a naive faith in data repositories: Versioning system repositories might seduce us with enchanting stories of always changing entities, but in reality many of these entities may just modify their make up and maintain their old behaviour; or issue repositories might tell us a partial truth about certain very special entities, or developers. We do agree with these researchers: Especially natural language documents contain information in different languages, surrounded by much noise. We must pay a special attention when using them.

We created MUCCA, a classification method to use when dealing with natural language documents. It recognizes source code fragments, patches, stack traces, noise, and natural language with significantly high accuracy. In this way, it allows one to subsequently apply ad hoc analysis techniques to exploit the peculiarities of each category, and extract reliable information.

This website supports the paper that describe our work on this topic.