Martin Ågren [off-list ref] 于2023年3月8日周三 15:47写道：

On Wed, 8 Mar 2023 at 07:50, ZheNing Hu [off-list ref] wrote:

quoted

My question is:
1. In step 3, why is the matrix size (a.nr + b.br) * (a.nr + b.br)
instead of a.nr * b.nr?

There's some explanation of that in the man page for `git range-diff`,
under "ALGORITHM". Look for "To explain also new commits, we introduce
dummy nodes on both sides:".

Thanks, I can understand why the length of the matrix is "a.nr + b.nr" now.
Patches in one collection may have no matching patches in the other
collection, this mismatch situation ("o--C" in the documentation) should
also count the cost.

quoted

2. Why the cost(x,y) which satisfies "x ∈ [a.nr, a.nr + b.nr) y ∈ [0,
b.nr) || x ∈ [0, a.nr) y ∈ [b.nr, b. The cost of nr + a.nr)" is set to
"diffsize(a or b) * creation_factor / 100 : COST_MAX"? What is the
role of creation_factor? [1]

The `--creation-factor` command line option is also described in the
manpage.  There was a thread on the mailing list with various
discussions around this creation factor a while back. Maybe there's
something interesting there [1].

I understand it now. Because mismatch "o--C" "1--0" cost are generally
greater than the cost of two completely different patches "1--C" "0--0".
Use the creation-factor to reduce the cost of "0-C" "1--0" make
"o--C", "1--0" as matching result.

quoted

3. How does LAPJV work here? [2]

[1]: https://github.com/git/git/blob/725f57037d81e24eacfda6e59a19c60c0b4c8062/range-diff.c#L310
[2]: https://github.com/git/git/blob/725f57037d81e24eacfda6e59a19c60c0b4c8062/linear-assignment.c#L15

This appears to be based on work by Jonker and Volgenant. Maybe
searching for those names online could find something. Maybe not
git-specific, but even if it's just the general algorithm as such, it
might be possible to find different explanations of the algorithm.

I haven't really studied this algorithm, but since it's faster than the
Hungarian algorithm, I could imagine that either

  * it's super-useful to first understand the Hungarian algorithm, then
    understand why and how the Jonker-Volgenant algorithm does better,
    or,

  * it's completely useless to first understand the Hungarian algorithm,
    since they're so different.

:-)

Ah, I had a look at the Hungarian algorithm earlier, because it is the most
typical algorithm in linear assignment problem, it can still be understood.
I didn't read that paper by Jonker and Volgenant, but I should try to read
it later.

[1] https://lore.kernel.org/git/1196830250.20220726145447@yandex.ru/ (local)

Martin

Thanks for the answer!

--
ZheNing Hu