git-tbdiff: topic branch interdiff
cp git-tbdiff.py /usr/local/bin/git-tbdiff # or anywhere else in $PATH, or in $(git --exec-path)
If your system does not yet have a
/usr/bin/python2 symlink (older
systems would only have
/usr/bin/python), you will need to edit the
git tbdiff A..B C..D
to compare the topic branch represented by the range A..B with that in the range C..D.
git tbdiff A...B
to let tbdiff automatically calculate the common ancestor X and compare the range X..A to X..B.
git tbdiff [--[no-]color] [--no-patches] [--creation-weight=<factor>] <range1> <range2> git tbdiff [--[no-]color] [--no-patches] [--creation-weight=<factor>] <committish1>...<committish2> git tbdiff [--[no-]color] [--no-patches] [--creation-weight=<factor>] <base> <topic1> <topic2>
tbdiff shows the differences between two versions of a patch series, or more generally, two sets of commits (ignoring merges). To do this in a meaningful way, it tries to find a good correspondence between commits in the two versions (see Algorithm below), and then shows the difference between the pairs found. It also copes with removal and addition of commits.
<range> arguments are passed unchanged and without any
validation to two git-log invocations.
Toggle colored output. The default is to use color.
Suppress the diffs between commit pairs that were deemed to correspond; only show the pairings.
Set the creation/deletion cost fudge factor to
<factor>. Defaults to 0.6. Try a larger value if tbdiff erroneously considers a large change a total rewrite (deletion of one commit and addition of another), and a smaller one in the reverse case. See the Algorithm section below for an explanation why this is needed.
Git does not ship with convenient tools for seeing the difference between versions of a topic branch. Some approaches seen in the wild include:
use git-cherry as a first-order comparison
rebase the old version on the new version to a) have the patch-id logic drop equivalent patches and b) [usually] get a conflict when the patches themselves differ on a change
apply on the same base
run interdiffs across the series
run an interdiff of the "squashed diff" (base to branch)
We propose a somewhat generalized approach based on interdiffs. The goal would be to find an explanation of the new series in terms of the old one. However, the order might be different, some commits could have been added and removed, and some commits could have been tweaked.
The general idea is this:
Suppose the old version has commits 1--2 and the new one has commits A--C. Assume that A is a cherry-pick of 2, and C is a cherry-pick of 1 but with a small modification (say, a fixed typo). Visualize the commits as a bipartite graph:
1 A 2 B C
We are looking for a "best" explanation of the new series in terms of the old one. We can represent an "explanation" as an edge in the graph:
1 A / 2 --------' B C
The 0 represents the edge weight; the explanation is "free" because there was no change. Similarly C can be explained using 1, but it has some cost c>0 because of the modification:
1 ----. A | / 2 ----+---' B | `----- C c>0
Clearly what we are looking for is some sort of a minimum cost bipartite matching; 1 is matched to C at some cost, etc. The underlying graph is in fact a complete bipartite graph; the cost we associate with every edge is the size of the interdiff between the two commits in question. To also explain new commits, we introduce dummy commits on both sides:
1 ----. A | / 2 ----+---' B | o `----- C c>0 o o o o
The cost of an edge o--C is the size of C's diff, modified by a fudge factor that should be smaller than 1. The cost of an edge o--o is free. The fudge factor is necessary because even if 1 and C have nothing in common, they may still share a few empty lines and such, making the assignment "1--C, o--o" may be slightly cheaper than "1--o, o--C" even if 1 and C have nothing in common. With the fudge factor we require a much larger common part to consider the patches related.
This definition allows us to find a "good" topic interdiff among topics with n and m commits in the time needed to compute n+m commit diffs and then n*m interdiffs, plus the time needed to compute the matching. For example, in this Python version we use the hungarian package, where the underlying algorithm runs in O(n^4). The matching found in this case will be like
1 ----. A | / 2 ----+---' B .--+-----' o -' `----- C c>0 o ---------- o o ---------- o
Then we reconstruct a "pretty" (well, not quite) output that represents the topic diff.