  Software development as done using modern methodologies and source control
management systems, has been often established as an example of
self-organization, with code growing and evolving organically, through
activities that do not stem from entralized power, leader or directives. The
main challenge in proving these claims is that self organization cannot be
detected through direct observation, but through measurements on the system,
looking for hints such as the existence of power laws over some features, such
as the size of changes over time. The problem we intend to tackle in this paper
is to establish a methodology for checking, for a chosen set of repositories we
had already measured in the past, if the claims about power laws actually hold
from a precise mathematical point of view, since, although shown as pervasive
in the software engineering literature (and others), power laws are more
elusive than they might seem at first sight. For that reason, in this paper we
present a statistically accurate set of tests that will help us decide, from
the way repositories are changing, if they are really distributed by a power
law, which could indicate us the existence of a state reached via
self-organization, or actually, how accurately a power law fits the observed
distribution of the size of changes of commits in git repositories of 16 open
source repositories. We revisit one of the most representative papers of these
observations to reevaluate its results and compare them with the current status
of the repositories analyzed in it, trying to elucidate if there has been any
change in the possible presence, or not, of a power law.
