Understanding Tree Structures in Computer Science: Types and Traversals Explained

Trees A tree's a tree. How many more do you need to look at? --Ronald Reagan

Tree Rules • One root • Each node may have 1 or more children • Each node except the root has exactly 1 parent • Moving up a tree to each parent leads to the root root parent leaf child leaf

Tree Example Root node Node with 2 children Node with right child Leaf node Node with left child

Tree Examples

Binary Tree Rules • One root • Each node can have a maximum of 2 child nodes • Left child • Right child • Each node except the root has exactly 1 parent • Moving up a tree to each parent leads to the root

Binary Search Tree • One root • Each node can have a maximum of 2 child nodes • Left child • Right child • The left child’s value is less than the node. • The right child’s value is greater than the node. • Each node except the root has exactly 1 parent • Moving up a tree to each parent leads to the root

Full Binary Tree • Every leaf has the same depth

Complete Binary Tree • All new leaves of a full binary tree are added from the left. • Add left-most nodes first

Heap • One root • Each node can have a maximum of 2 child nodes • Left child • Right child • Complete binary tree • Every node must have max children except… • Leaf level can be incomplete if all nodes are as far left as possible • The node’s value is >= the value of its children • The left child’s value is less than (or equal to) the node. • The right child’s value is less than (or equal to) the node. • Each node except the root has exactly 1 parent • Moving up a tree to each parent leads to the root

B Tree • One root • Each node can have MINIMUM entries (key indices) for children nodes up to twice the value of MINIMUM for a single node. • The entries are stored in an array, sorted from the smallest to largest • The number of subtrees below a nonleaf node is always one more than the number of entries in the node. • For any nonleaf node an entry at index i is greater than all the entries in subtree number i of that node and an entry at index i is less than all the entries in subtree number i+ 1 of the node. • Data items are only stored in leaves • All leaves have the same depth • Each node except the root has exactly 1 parent • Moving up a tree to each parent leads to the root

Tree Traversals (pp 500) • Climbing all nodes of a tree • Traversals are named by when the root is processed and “root” implies all roots of all subtrees • Pre-order traversal • In-order traversal • Post-order traversal

Pre-Order Traversal • Root is processed previous to its subtrees • 1. process root • 2. process nodes in left subtree recursively • 3. process nodes in right subtree recursively template <class Item> void preorder_print(binary_tree_node <Item>* node_ptr) { if (node_ptr != NULL) { //1. process root std::cout << node_ptr->data() << std::endl; //2. process left preorder_print(node_ptr->left()); //3. process right preorder_print(node_ptr->right()); } }

In-Order Traversal • Root is processed between its subtrees • 1. process nodes in left subtree recursively • 2. process root • 3. process nodes in right subtree recursively template <class Item> void inorder_print(binary_tree_node <Item>* node_ptr) { if (node_ptr != NULL) { //1. process left inorder_print(node_ptr->left()); //2. process root std::cout << node_ptr->data() << std::endl; //3. process right inorder_print(node_ptr->right()); } }

Post-Order Traversal • Root is processed after its subtrees • 1. process nodes in left subtree recursively • 2. process nodes in right subtree recursively • 3. process root template <class Item> void postorder_print(binary_tree_node <Item>* node_ptr) { if (node_ptr != NULL) { //1. process left postorder_print(node_ptr->left()); //2. process right postorder_print(node_ptr->right()); //3. process root std::cout << node_ptr->data() << std::endl; } }

Understanding Tree Structures in Computer Science: Types and Traversals Explained