Figure %: After adding "Steve" to the table
And "Spark" which hashes to 6:
Figure %: After adding "Spark" to the table
Now we add "Notes" which hashes to 3, just like "Steve":
Figure %: Collision solved - "Notes" added to table
Once we have our hash table populated, a search follows the same steps as
doing an insertion. We hash the data we're searching for, go to that place
in the array, look down the list originating from that location, and see if
what we're looking for is in the list. The number of steps is O(1).
Separate chaining allows us to solve the problem of collision in a simple
yet powerful manner. Of course, there are some drawbacks. Imagine the
worst case scenario where through some fluke of bad luck and bad programming,
every data element hashed to the same value. In that case, to do a lookup,
we'd really be doing a straight linear search on a linked list, which means
that our search operation is back to being O(n). The worst case search
time for a hash table is O(n). However, the probability of that happening
is so small that, while the worst case search time is O(n), both the best
and average cases are O(1).