discrepancy in alpha-beta

I noticed some pseudocode from wikipedia
(http://en.wikipedia.org/wiki/Alpha-beta_pruning) that does these
checks in alpha beta:

min:
if beta <= alpha return alpha

max:
if beta <= alpha return beta

Then there's code at
http://www.cs.dartmouth.edu/~rus/courses/AI/AI-03/Lectures/l6.html that
says this:

min:
If beta >= alpha return alpha

max:
If alpha >= beta return beta


As you can see, the checks for min differ. Anyone know who's right?

When alpha < beta, things are "normal". When alpha >= beta, the current
path can be pruned.

When you are maximizing, you are trying out a bunch of potential moves
for max, which means you are looking at a bunch of new alpha values.
Then you test a new alpha value against the current beta value. So if
you find a violation of alpha < beta, you return the alpha immediately.

When you are minimizing, you are trying out a bunch of of new beta
values associated with min's move. Here you test the current alpha
value against each new beta value. If you find one that violates alpha
< beta, you return it immediately.

So it looks like Wikipedia is correct here, and the test for min
in the Dartmouth notes is in error (possibly a typo).

Mike