Use machine learning and natural language processing techniques to analyze the changes made in a project, and classify them in: * Small / unimportant fix

It is well-known that two git commits within a single repo can be independent from each other, by changing separate files to each other, or changing separate parts of the same file(s). Conversely when a commit changes a line, it is "dependent" on not only the commit which last changed that line, but also any commits which were responsible for providing the surrounding lines of context, because without those previous versions of the line and its context, the commit's diff would not cleanly apply. As with most dependency relationships, these form a directed acyclic graph. Sometimes it is useful to understand the nature of parts of this graph; for example when porting a commit "A" between git branches via git cherry-pick, it can be useful to programmatically determine in advance the minimum number of other dependent commits which would also need to be cherry-picked to provide the context for commit "A" to cleanly apply.