That's clearer asciidoc formatting. Signed-off-by: Jean-Noël Avila <jn.avila@xxxxxxx> --- Documentation/git-bisect-lk2009.txt | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/Documentation/git-bisect-lk2009.txt b/Documentation/git-bisect-lk2009.txt index 3ba49e85b7..f3d9566c89 100644 --- a/Documentation/git-bisect-lk2009.txt +++ b/Documentation/git-bisect-lk2009.txt @@ -473,7 +473,7 @@ Z-Z ------------- 2) starting from the "good" ends of the graph, associate to each -commit the number of ancestors it has plus one + commit the number of ancestors it has plus one For example with the following graph where H is the "bad" commit and A and D are some parents of some "good" commits: @@ -514,7 +514,7 @@ D---E ------------- 4) the best bisection point is the commit with the highest associated -number + number So in the above example the best bisection point is commit C. @@ -580,8 +580,8 @@ good or a bad commit does not give more or less information). Let's also suppose that we have a cleaned up graph like one after step 1) in the bisection algorithm above. This means that we can measure -the information we get in terms of number of commit we can remove from -the graph.. + the information we get in terms of number of commit we can remove + from the graph.. And let's take a commit X in the graph. @@ -689,18 +689,18 @@ roughly the following steps: 6) sort the commit by decreasing associated value 7) if the first commit has not been skipped, we can return it and stop -here + here 8) otherwise filter out all the skipped commits in the sorted list 9) use a pseudo random number generator (PRNG) to generate a random -number between 0 and 1 + number between 0 and 1 10) multiply this random number with its square root to bias it toward -0 + 0 11) multiply the result by the number of commits in the filtered list -to get an index into this list + to get an index into this list 12) return the commit at the computed index -- 2.28.0.rc0
