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Learning Tree Data structure [Java]
Rating: 4.7 out of 5(16 ratings)
1,928 students

Learning Tree Data structure [Java]

Breadth First Search and Depth First Search in Trees
Created byMonish Njs
Last updated 2/2023
English

What you'll learn

  • Clear understanding of Tree Data structure
  • How to use Breadth First Search in Tree Data structure
  • How to use Depth First Search in Tree Data structure
  • Visualize the Code flow using Debugger in Leetcode

Course content

2 sections6 lectures51m total length
  • Level Order Traversal13:05
  • ZigZag traversal of tree5:44
  • Right view of Tree4:07

Requirements

  • knowledge on LinkedList is needed

Description

Course Description:

This course explains how we can solve problems involving Tree data structure. First, the concept is explained in white board and then the solution is coded for better understanding.

When we see a tree data structure, the first thing we need to identify is to use either Breadth-first Search or Depth-first search. This course differentiates the Breadth-first search and Depth-first search problems and the different techniques used in them.

Depth First search uses recursion. It is very hard to visualize recursion. This course uses a debugger and this helps in visualizing the code flow.


What is Tree data structure?

A tree is non-linear and a hierarchical data structure consisting of a collection of nodes such that each node of the tree stores a value and a list of references to other children nodes .

Applications :

  1. Store hierarchical data, like folder structure, organization structure, XML/HTML data.

  2. Binary Search Tree is a tree that allows fast search, insert, delete on a sorted data. It also allows finding closest item

  3. Heap is a tree data structure which is implemented using arrays and used to implement priority queues.

  4. B-Tree and B+ Tree : They are used to implement indexing in databases.

  5. Syntax Tree: Scanning, parsing , generation of code and evaluation of arithmetic expressions in Compiler design.

  6. Trie : Used to implement dictionaries with prefix lookup.

  7. Suffix Tree : For quick pattern searching in a fixed text.

  8. Spanning Trees and shortest path trees are used in routers and bridges respectively in computer networks

    etc

Who this course is for:

  • Beginner and People who find hard to work on Tree data structures can take this course