CPT-Graphs-directed-weighted-ex1.svg

Simple AVL Tree in C++

An AVL tree is a binary search tree(BST) however, unlike binary search trees, an AVL tree (named after Georgy Adelson-Velsky and Evgenii Landis) is self balancing. So no matter how many nodes you insert into the tree, it will adjust it’s branches and ensure the tree is balanced at all times. Making sure the subtree heights only differ by at most 1. BSTs are great for segregating and storing data with a O(log n) search time. Downside with BST is that it can get weighted on one side and doesn’t have an restrictions to prevent it from getting skewed. By switching to an AVL, data is balanced in the tree and the search time is decreased to log n.

So it is more efficient in most cases to use the AVL tree, below is an example of how to code this in C++. Note that the AVL tree uses a lot of the same code the BST did from this post.

#pragma once

#include <iomanip>
#include <iostream>

using namespace std;

class AVL
{
public:
    AVL(){
        root = nullptr;
    }
    ~AVL(){
        destroy(root);
    }
    
    //My Node class for storing data, note how I add height
    struct Node{
        int data;
        Node *left;
        Node *right;
        int height;

        Node(int d){
            data = d;
            left = nullptr;
            right = nullptr;
            height = 0;
        }

        void updateHeight(){
            int lHeight = 0;
            int rHeight = 0;
            if (left != nullptr) {
                lHeight = left->height;
            }
            if (right != nullptr) {
                rHeight = right->height;
            }
            int max = (lHeight > rHeight) ? lHeight : rHeight;
            height = max + 1;
        }

    };

    void insert(int val){
        insert(val, root);
    }

    //Rotate a Node branch to the left, in order to balance things
    Node* rotateLeft(Node *&leaf){
        Node* temp = leaf->right;
        leaf->right = temp->left;
        temp->left = leaf;

        //update the Nodes new height
        leaf->updateHeight();

        return temp;
    }

    //Rotate a Node branch to the right, in order to balance things
    Node* rotateRight(Node *&leaf){
        Node* temp = leaf->left;
        leaf->left = temp->right;
        temp->right = leaf;

        //update the Nodes new height
        leaf->updateHeight();

        return temp;
    }

    //Rotate a Node branch to the right then the left, in order to balance things
    Node* rotateRightLeft(Node *&leaf){
        Node* temp = leaf->right;
        leaf->right = rotateRight(temp);
        return rotateLeft(leaf);
    }

    //Rotate a Node branch to the left then the right, in order to balance things
    Node* rotateLeftRight(Node *&leaf){
        Node* temp = leaf->left;
        leaf->left = rotateLeft(temp);
        return rotateRight(leaf);
    }

    //Function that checks each Node's left and right branches to determine if they are unbalanced
    //If they are, we rotate the branches
    void rebalance(Node *&leaf){
        int hDiff = getDiff(leaf);
        if (hDiff > 1){
            if (getDiff(leaf->left) > 0) {
                leaf = rotateRight(leaf);
            } else {
                leaf = rotateLeftRight(leaf);
            }
        } else if(hDiff < -1) {
            if (getDiff(leaf->right) < 0) {
                leaf = rotateLeft(leaf);
            } else {
                leaf = rotateRightLeft(leaf);
            }
        }
    }

private:
    Node *root;
    //Insert a Node (very similar to BST, except we need to update Node height and then check for rebalance)
    void insert(int d, Node *&leaf){
        if (leaf == nullptr){
            leaf = new Node(d);
            leaf->updateHeight();
        }
        else {
            if (d < leaf->data){
                insert(d, leaf->left);
                leaf->updateHeight();
                rebalance(leaf);
            }
            else{
                insert(d, leaf->right);
                leaf->updateHeight();
                rebalance(leaf);
            }
        }
    }

    //Same as BST
    void destroy(Node *&leaf){
        if (leaf != nullptr){
            destroy(leaf->left);
            destroy(leaf->right);
            delete leaf;
        }
    }
    
    //Get the difference between Node right and left branch heights, if it returns positive
    //We know the left side is greater, if negative, we know the right side is greater
    int getDiff(Node *leaf){
        int lHeight = 0;
        int rHeight = 0;
        if (leaf->left != nullptr) {
            lHeight =  leaf->left->height;
        }
        if (leaf->right != nullptr) {
            rHeight = leaf->right->height
        }
        return lHeight - rHeight;
    }
};

Let me know if you have any issues!

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Binary Search Tree Traversals in C++

So this will pretty much wrap up our short expedition into binary trees. Remember that these functions rely on my earlier posts dealing with the class and nodes.

The three types of traversals we will look at are:

  • Preorder (root, left, right)
  • Inorder (left, root, right)
  • Postorder (left, right, root)

Preorder Traversal

This type of traversal can be used to create duplicates of a tree and can be used to implement prefixes. Whatever order of values you put into a tree will be the order that preorder traversal gives you. So If I enter, 5 7 4 2 1 9 8 3 6 into a binary tree, when I use preorder traversal, I will expect to see 5 7 4 2 1 9 8 3 6.

void preorderTraversal (Node* n) {
    if (n != nullptr) { //make sure we have a value
        cout << n->data << endl; //Print out the current Node value
        preorderTraversal(n->left); //traverse down the left side
        preorderTraversal(n->right); //Once we return from the left, go down the right
    }
}

Inorder Traversal

This type of traversal will return data sorted in order. So if I entered, 5 7 4 2 1 9 8 3 6, I would expect to see 1 2 3 4 5 6 7 8 9.

  void inorderTraversal (Node* n) {
    if (n != nullptr) { //make sure we have a value
        inorderTraversal(n->left); //traverse down the left side
        cout << n->data << endl; //Print out the current Node value
        inorderTraversal(n->right); //Once we return from the print, go down the right
    }
}

Postorder Traversal

This type of traversal can be used to implement postfixes and can cleanly be used to destroy a tree with out leaving Nodes floating around corrupting memory. So if I entered, 5 7 4 2 1 9 8 3 6, I would expect to see 1 3 2 4 6 8 9 7 5

 void postorderTraversal (Node* n) {
    if (n != nullptr) { //make sure we have a value
        postorderTraversal(n->left); //traverse down the left side
        postorderTraversal(n->right); //Once we return from the left, go down the right
        cout << n->data << endl; //Print out the current Node value
    }
}

For more information on binary trees, I would checkout this article. It goes into detail on how traversals on called on the tree and gives some great visuals. I also liked this interactive visual for binary search trees in general.

Good luck!

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Sweet Binary Search Tree Print in C++

I found the basis of a print on Stackover flow the other day and changed it a little bit to be more compatible across compiler versions.

Happy Coding!

void print() {
    print(root, 0); //call it on your root/head node
}

For some reason my code editor wouldn’t do the left slashes so below is a screenshot.

Here is an example of what it will look like for the sequence 5 7 4 2 1 9 8 3 6:

CPT-Graphs-directed-weighted-ex1.svg

Binary Search Trees! Simple Class in C++

Here is a really basic binary tree class, it just includes the basics of creating, inserting, erasing, and returning size. In later posts I will talk about printing and traversals.

This class also uses the Node.h talked about in this earlier post. You’ll notice that I really like to use recursion, I think this is cleaner than looping.

#include <assert.h>
#include "Node.h"
using namespace std;

class Bst
{
    public:

        //constructor for when a head Node is provided and when it is not
        Bst() {
            root = nullptr;
        }

        Bst(Node *np) {
            root = np;
        }

        //destroy the tree, we need to go through and destroy each node
        ~Bst() {
            destroyTree(root);
        }

        //get the number of nodes in the tree
        int size() {
            return size(root);
        }

        //erase a value in the tree
        void erase(int item) {
            erase(item, root);
        }

        //insert a Node in the tree
        void insert(int item) {
            insert(item, root);
        }

    private:

        Node* root;

        //Go through each branch and recursively destroy all Nodes
        void destroyTree(Node*& n) {
            if (n != nullptr) {
                destroyTree(n->left);
                destroyTree(n->right);
                delete n;
            }
        }

        //For each Node return the number of left and right nodes
        //Add it up recursively to get the total size
        int size(Node* n) {
            if (n != nullptr) {
                int left = size(n->left);
                int right = size(n->right);
                int self = 1;
                return left + self + right;
            }
            return 0;
        }

        //Find the minimum Node value
        Node* findMin(Node* n){
            assert(n != nullptr);
            if (n->left != nullptr) {
                return findMin(n->left);
            }
            return n;
        }

        //this one is a beast
        //look through all the nodes recursively
        //once you find the node value there are numerous cases we need to look for
        //If the current node does not have left and right nodes, just delete it
        //If it does have a left or right node, set the child to the parent
        //If it has both left and right, we need to work some magic. First we find
        //the smallest value and set the node we want to delete to that value (removing it)
        void erase(int item, Node*& n) {
            if (n != nullptr) {
                if (item == n->data) {
                    if (n->right == nullptr && n->left == nullptr) {
                        delete n;
                        n = nullptr;
                    } else if (n->right == nullptr) {
                        Node* temp = n;
                        n = n->left;
                        delete n;
                    } else if (n->left == nullptr){
                        Node* temp = n;
                        n = n->right;
                        delete n;
                    } else {
                        Node *temp = findMin(n->right);
                        n->data = temp->data;
                        erase(item, n->right);
                    }
                } else if (item < n->data) {
                    erase(item, n->left);
                } else {
                    erase(item, n->right);
                } 
            }
        }

        //look through all the nodes
        //insert the node on the correct node, it will be added to the left if the value is less
        //added to the right if the value is greater
        void insert(int item, Node*& n) {
            if (n != nullptr) {
                if (item < n->data) {
                    insert(item, n->left);
                } else {
                    insert(item, n->right);
                }
            } else {
                n = new Node(item);
            }
        }
};

Let me know if you have any improvements or comments!