Data Types:
To start storing based on the type the DATA belongs too.
Strongly Typed vs Loosely Typed:
Strongly Types: The languages that ask to have or mention the type of the Data. Example: c++, java
Loosely Typed: The languages that not necessarily ask to have or mention the type of the Data.
Example: php, perl, js
In this contrary of building, processing Data, there goes the story for Data Structures to:
Store
Retrieve
Process
the Data.
We need:
- Efficient procedures which is the start of Complexity Measure
Complexity:
Measure through: Memory & Operations ongoing.
Big(O)
Arrays:
Homogeneous Collection of Data
Real-Life Examples: Tea-Tray & Cups
Structure: Linear, Sequential
Type of access: (Static) Fixed Length
Requires: index, value
Operations: insert, update, delete, retrieve
Stack Queue: (LIFO)
Adding Deleting element from last.
Re al-Life Examples: Pack of books.
LinkedList:
create Node
TREE
Root on Top
Binary Tree: node have left right chilren
BST: left small right big (sorted tree)
Heap (Complete binary tree)
TRIE(for Alphabets)
auto complete, dictionary
Map(easy access of elements)
key-value pairs
Ordered, Unordered
Set
Graph
