16.2 Binary Search Trees

Linked Lists are great, but it takes a long time to search for an item, even if the list is sorted! What if the item is at the end of the list? That would take linear time!

We know that for an array, we can use binary search to find an element faster. Specifically, in $\log n$ time. For a short explanation of binary search, check out this link.

In binary search, we know the list is sorted, so we can use this information to narrow our search. First, we look at the middle element. If it is bigger than the element we are searching for, we look to the left of it. If it is smaller than the element we are searching for, we look to the right. We then look at the middle element of the respective halves and repeat the process until we find the element we are looking for (or don't find it because the list doesn't contain it).

But how do we run binary search for a linked list? We would have to traverse all the way to the middle in order to check the element there, which takes linear time just on its own!

One optimization we can implement is to have a reference to the middle node. This way, we can get to the middle in constant time. Then, if we flip the nodes' pointers, which allows us to traverse to both the left and right halves, we can decrease our runtime by half!

A linked list with a middle pointer

But we can further optimize by adding pointers to the middle of each recursive half like so. Now, if you stretch this structure vertically, you will see a tree! This specific tree is called a binary tree because each juncture splits in 2.

A linked list with recursive middle pointers is a binary tree!