For anyone interested in more discussion of this I suggest grabbing a copy of "Making Software", in particular chapter eleven on Conways Corollary which the cha

For anyone interested in more discussion of this I suggest grabbing a copy of "Making Software", in particular chapter eleven on Conways Corollary which the chapter centered around this paper from 2008 http://research.microsoft.com/pubs/70535/tr-2008-11.pdf http://research.microsoft.com/pubs/70535/tr-2008-11.pdf The meat: Table 4: Overall model accuracy using different software measures Precision Recall Model 86.2% 84.0% Organizational Structure 78.6% 79.9% Code Churn 79.3% 66.0% Code Complexity 74.4% 69.9% Dependencies 83.8% 54.4% Code Coverage 73.8% 62.9% Pre-Release Bugs Or in plain terms if people mess with code they don't normally mess with, you can bet real money (with a higher probability than other metrics) it introduces bugs. Edit: I have been meaning to make a git tool that would analyze the history of a project to create predictions on what bit of code is the most buggy using this model, but just haven't done it yet. It would be cool to integrate it with GitHub's bugs api to see how correct it might be. If someone does make it let me know!