Revise different data structures in C# and solve related coding problems for better understanding.

Ace the C# Coding Interview

This module contains a detailed review of all the common data structures, and it also provides implementation-level details in C# to help us become well-equipped with different data structures that we can leverage to write better code!
This module will help us understand basic data structures such as arrays, linked lists, stacks, queues, trees, trie, hashing, and graphs. Every concept is followed by several coding challenges along with their solutions.

Data Structures for Coding Interviews in C#

# Introduction

In 1962, AVL was named after the inventors, Adelson-Velsky and Landi. They claimed that AVL trees are: “An algorithm for the organization of  information." They are binary search trees such that for every internal node $v$ of the tree $T$, the heights of $v$'s children can differ by at most $1$. To put it simply, for each node, the height of the left and right-subtrees in an AVL tree can differ at most by one or the tree is *balanced*.  If at any point, their difference becomes more than one, then steps are taken to rebalance the tree. 

# Time complexity

In the case of binary search trees, the time complexity of all three basic operations, insertion, deletion, and search take $O(h)$ time, where *"h"* is the height of the binary search tree. The worst-case time complexity is $O(n)$ for skewed BSTs where *"n"* is the number of nodes in the tree. This is the same as an array or list. However, in the best case, when the tree is completely balanced, the time complexity for basic operations is $O(log(n))$. AVL trees are essentially BSTs in the best-case. 

The following diagram is an example of a valid AVL Tree.

This lesson has a brief introduction to AVL trees, why they are used, and what makes them more efficient than regular binary search trees.

What is an AVL Tree?

Introduction