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.