Data Structures From Scratch

Explore dynamic linked lists by learning how nodes store data and a next pointer, enabling memory-based growth, efficient insertion and deletion, and flexible, size-unbounded structures.

Demonstrate inserting a new element at the end of a linked list and updating the last pointer and connections.

Learn how to delete a node from a linked list by updating the previous node next pointer and freeing the removed node memory.

Explore dynamic stacks using a linked list, replacing static allocation limits with a flexible structure. Learn push and pop operations, top-at-beginning insertion, and constant-time access on the head-backed stack.

Explore how stacks apply to arithmetic expressions, covering operator precedence, infix versus postfix notation, and examples of evaluating and organizing expressions with stacks.

Define a queue as a first-in, first-out data structure where elements enqueue at the back and dequeue from the front, with isEmpty, front, back, and static or dynamic implementations.

Explore the basics of trees and binary trees, including root nodes, left and right children, leaves, and siblings, plus complete and almost complete trees and level-based node counts.

Construct a binary expression tree for an arithmetic expression, convert infix to postfix with a stack, and use preorder and postorder traversals for prefix and postfix notations.

Implementing binary trees teaches building binary search trees in C++, including insert, search, check empty, and node counting, with height and recursion concepts.

Learn to search for an item in a binary search tree by comparing the target with the current node and moving left or right, including handling of an empty tree.

Learn how to insert nodes into a binary search tree by comparing values and following left or right links, while understanding BST properties and practical examples.

Explore how AVL trees maintain balance to keep binary search trees efficient, compare balanced and unbalanced structures, and examine how insertion and deletion affect height.

avl trees balance binary search trees using rotations to keep height small, preventing unbalanced structures after insertions or deletions and speeding up search operations.

Explore how AVL trees maintain balance after insertion by applying single and double rotations, using balance factors to correct unbalanced cases.

Explore a C++ AVL tree implementation, showing how to maintain node height during insertion, compute balance factors, and apply rotations to keep the tree balanced.