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).
@@ -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:
@@ -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