  Although information theory has found success in disciplines, the literature
on its applications to software evolution is limit. We are still missing
artifacts that leverage the data and tooling available to measure how the
information content of a project can be a proxy for its complexity. In this
work, we explore two definitions of entropy, one structural and one textual,
and apply it to the historical progression of the commit history of 25 open
source projects. We produce evidence that they generally are highly correlated.
We also observed that they display weak and unstable correlations with other
complexity metrics. Our preliminary investigation of outliers shows an
unexpected high frequency of events where there is considerable change in the
information content of the project, suggesting that such outliers may inform a
definition of surprisal.
