@@ -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
That's clearer asciidoc formatting. Signed-off-by: Jean-Noël Avila <jn.avila@free.fr> --- Documentation/git-bisect-lk2009.txt | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-)