Data Structures Cookbook

References:
https://www.geeksforgeeks.org/real-time-application-of-data-structures/
https://www.programiz.com/dsa

Arrays:

Single Dimensional or Linear Arrays:
Applications:
a) For sorting data elements.
b) Implement Stacks and Queues

Multi Dimensional Arrays:
Applications:
a) Used for plotting graphs, and statistics and also to do scientific studies and research in almost different fields
b) Best representation methods for plotting surveys
c) Matrix Calculations.

LinkedList:

Applications:
a) Web pages can be accessed using the previous and the next URL links which are linked using a linked list.
b) Train coaches are connected to one another in a doubly-linked list fashion.
c) Social media content “feeds”.

Stacks: First in Last Out

Applications:
a) Message logs and all messages you get are arranged in a stack.
b) History of visited websites.
c) Syntaxes in languages are parsed using stacks.
d) Call stacks in programming run times.

Queues: First in First Out

Applications:
a) For job scheduling.
b) Sending an e-mail, it will be queued.
c) Data packets in communication are arranged in queue format

Priority Queue:

Reference: https://www.programiz.com/dsa/priority-queue

A priority queue is a special type of queue in which each element is associated with a priority value. And, elements are served on the basis of their priority. That is, higher priority elements are served first.
Note: If elements with the same priority occur, they are served according to their order in the queue.

Difference between Priority Queue and Normal Queue

In a queue, the first-in-first-out rule is implemented whereas, in a priority queue, the values are removed on the basis of priority. The element with the highest priority is removed first.

Applications:
1) Premium user requests
2) VVIP,VIP tickets, requests etc.

Graph:

Data structure where data is stored in a collection of interconnected vertices (nodes) and edges (paths).

Applications:
a) Recommendation Engines.
b) The GPS navigation system also uses shortest path APIs.
c) GraphQL queries.

Trees:

It is a graph without cyclic paths.

Applications:
a) Domain Name Server(DNS) also uses tree structures.
b) XML structure
c) File explorer/my computer of mobile/any computer

Binary Search Tree:

Reference: https://www.programiz.com/dsa/binary-search-tree
Each node has a maximum of two children.
It is called a search tree because it can be used to search for the presence of a number in O(log(n)) time.

The properties that separate a binary search tree from a regular binary tree is

1. All nodes of left subtree are less than the root node
2. All nodes of right subtree are more than the root node
3. Both subtrees of each node are also BSTs i.e. they have the above two properties

Applications:
a) Used for indexing and multi-level indexing.
b) Computer Graphics Rendering

Trie:

Applications:
1) Dictionary
2) Autocomplete

Hash Tables:

The Hash table data structure stores elements in key-value pairs where

• Key- unique integer that is used for indexing the values
• Value — data that are associated with keys.

Note: Since Hash of of 2 input string can be same, we shouldn’t replace the existing key, value pair, and this is called as Collusion Resolution.
Chaining: Value is a doubly linked-list. Each data is stored as a node in this doubly linked list.

Applications:
a) Indexing data
b) Constant time lookup and insertion is required
c) Cryptographic applications

Heaps:

min heap: the key of the parent is less than or equal to those of its children max heap: the key of the parent is greater than or equal to those of its children

Applications:
a) Implementing a priority queue.
b) Dijkstra’s Algorithm
c) Heap Sort