Summary

This chapter went deep into trees, starting off with the simplest form: the binary search tree. This tree prepares the inserted data for search by creating a left and a right branch which hold smaller or greater values. A search algorithm can therefore just pick the direction based on the current node and the value coming in, thereby skipping a majority of the other nodes.

The regular binary search tree has a major drawback, however: it can become unbalanced. Red-black trees provide a solution for that: by rotating subtrees, a balanced tree structure is maintained and search performance is guaranteed.

Heaps are a more exotic use of the tree structure. With their primary use as a priority queue, they efficiently produce the lowest or highest number of an array in constant time. The upheap and downheap operations repair the structure upon insert or removal so that the root is again the lowest (min-heap) or highest (max-heap) number.

Another very exotic structure is the trie. They are...