Read 15 ~ Trees

By Abdallah obaid

NAME	URL
Home	Home.
Prep	Prep: Engineering Topics.
Read 01	Node Ecosystem, TDD, CI/CD.
Read 02	Classes, Inheritance, Functional.
Read 03	Data Modeling & NoSQL Databases.
Read 04	Advanced Mongo/Mongoose.
Read 05	Linked Lists.
Read 06	HTTP and REST.
Read 07	Express.
Read 08	Express Routing & Connected API.
Read 09	API Server.
Read 10	Stacks and Queues.
Read 11	Authentication.
Read 12	OAuth.
Read 13	Bearer Authorization.
Read 14	Access Control (ACL).
Read 15	Trees.
Read 16	Event Driven Applications.

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Trees

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## Trees:

• A tree data structure can be defined recursively as a collection of nodes (starting at a root node), where each node is a data structure consisting of a value, together with a list of references to nodes (the “children”), with the constraints that no reference is duplicated, and none points to the root.
• Trees are good for reducing the search time for an element within the container.

• Tree: could be traversals by: Depth First

  Breadth First.

• Depth-first divided into three different methods:
  1. Pre-order: root » left » right
  2. In-order: left » root » right
  3. Post-order: left » right » root
• Breadth-first traversal iterates through the tree by going through each level of the tree node-by-node. So, given our starting tree one more time.

## Common Tree Terminology:

• Node - individual item/data that makes up the data structure.
• Root - the first/top Node in the tree.
• Left Child - The node in the left of a root or node.
• Right Child - The node in the right of a root or node.
• Edge - link between a parent and child node.
• Leaf - node that does not contain any children.
• Height - number of edges from the root to the bottommost node

## Binary Tree Data Structure :

• A tree whose elements have at most 2 children is called a binary tree. Since each element in a binary tree can have only 2 children, we typically name them the left and right child.