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“ For solving any real world problem with a programming approach we need to follow some steps. Collection of that steps is Algorithm, whereas a data structure is a way to store and organize data in a computer,so that it can be used efficiently in terms of time and space, so Data structure & Algorithms always allow us to write efficient and optimized computer programs.”

• Reference for this repo is taken fromABDUL SIR course

• STL is standard template library, It is most powerful & useful while doing competitive coding questionsRead More.

• Problems on Data structure & Algorithms (Competitive coding)Click Here to get into problems section.

• 📘 Recursion

  • 01 Head Recursion
  • 02 Tail Recursion
  • 03 Global variable recursion
  • 04 Static variable reciursion
  • 05 Tree recursion
  • 06 Nested recursion
  • 07 Sum of n number using recursion
  • 08 Sum Of given number using loop
  • 09 Power using recursion
  • 10 Taylor Series using Static variables
  • 11 Taylor Series honers rule
  • 12 Taylor Series Iterative
  • 13 Indirect Recursion
  • 14 Fibbonaci series using loop and recursion
  • 15 Fibbonacci using Memoization
  • 16 nCr formula
  • 17 Tower of Hanoi

• 📘Array

  • 01 Static and dynamic array
  • 02 Increasing size of array in heap
  • 03 Creating 2D array & Accessing
  • 04 Array ADT1
  • 05 inserting an element
  • 06 Deleting element
  • 07 Linear search
  • 08 Improving Linear search
  • 09 Binary Search Using Recursion
  • 10 Binary Search using loop
  • 11 Get Set max min sum avg
  • 12 Rotate and Shift
  • 13 IsSorted
  • 14 Mergeing 2 Array
  • 15 InsertSort
  • 16 Set Operation (Union,Intersec,diff)
  • 17 Insertion and Deletion
  • 18 Menu Based problem
  • 19 Single Missing Element in Sorted Array
  • 20 Single Missing Value in a sorted array M2
  • 21 Multiple Missing Elements in Sorted Array
  • 22 Missing elements in Unsorted Array (HASH TABLE)
  • 23 Finding Duplicate in Soorted Array
  • 24 Counting Duplicate Elements In Sorted M2
  • 25 Counting Duplicate elements using hash table (SA)
  • 26 Counting Duplicate elements using hash table (USA)
  • 27 Finding Duplicate in Unsoorted Array
  • 28 Find a pair with sum k
  • 29 Find a pair with sum k in unsorted
  • 30 Find a pair with sum k using Hashing
  • 31 Finding max & min in single scan
    • Problems on array

• 📘String

  • 01 Length of string
  • 02 Upper to Lower
  • 03 lower to upper
  • 04 Upper to Lower & Lower to upper
  • 05 Vowel & Counstant count
  • 06 Word Count
  • 07 Reverse the string

• 📘Linkedlist

  • 01 Display LL
  • 02 Display LL Using Recursion
  • 03 Count and sum of LL
  • 04 Printing max element
  • 05 Searching Element
  • 06 Searching Elements using Recursion & Move to 1st
  • 07 Insertion in linkedlist
  • 08 Insert in sorted
  • 09 All in one 1 to 8
  • 10 project sll
  • 11 Delete from ll.
  • 12 Remove duplicate
  • 13 Reversing Using Array
  • 14 Reversing by Sliding Links
  • 15 Reversing using Recursion
  • 16 Concatenate linkedlist
  • 17 Merge LL
  • 18 Liner Singly Linked List in Single Project
  • 19 Display Circular LL using Loop & Recursion
  • 20 Insert in Circular LL
  • 21 Delete from cll from pos
  • 22 Delete an element in CLL from pos
  • 23 Create,Display,count DLL
  • 24 Insert at any pos in dll
  • 25 Delete from any pos from DLL
  • 26 Reverse DLL
  • 27 Middle of Linkedlist
  • 28 Polynomial of Linkedlist
    • Problems on LL

• 📘Stack

  • 01 Operation on stack
  • 02 Stack using linkedlist
  • 03 Parenthesis Balance
  • 04 Infix to postfix
  • 05 infix to postfix considering Parenthesis and Associativity using Stack
  • 06 Evaluation of postfix expression

• 📘Queue

  • 01 Queue using array enqueue & dequeue
  • 02 C++ Queue using Array
  • 03 Circular Queue using Array
  • 04 C++ Circular Queue
  • 05 Queue using Linkedlist
  • 06 DEQueue using Array
  • 07 Queue using two stack

• 📘Tree

  • 01 Traversal of tree
  • 02 Iterative and recursive traversal of tree
  • 03 Traversal of Tree
  • 04 Level Order Traversal
  • 05 Count and Height of tree
  • 06 Recursive Count and height of tree
  • 07 Sum of tree
  • 08 D1,D2,D0(leaf node) count
  • 09 Leaf,D1,D2 node count

• 📘Binary Search Tree

  • 01 BST Insert Inorder & Search
  • 02 BST Insert,Inorder&Search(cpp)
  • 03 Insert in BST
  • 04 Recursive Insert in BST
  • 05 Delete from BST (Height,InPre,InSucc)
  • 06 BST Project

• 📘AVL Tree

  • 01 Rotations in AVL(LL,LR)
  • 02 Rotation in AVL
  • 03 Delete From AVL
    • Problems on Tree

• 📘Graph

  • 01 BFS
  • 02 DFS
  • 03 PrimMinSpanningTreeFunction
  • 04 KrushalsMinCostSpanningTreeFunction
  • 05 DepthFirstSearchUsingRecursion
  • 06 BreadthFirstSearchUsingSTLQueue

• 📘Heap

  • 01 InsertionHeap
  • 02 CreateHeapUsingSTLVector
  • 03 Insert in Heap
  • 04 Delete element from Heap
  • 05 Heap sort
  • 06 HeapifyFunctionFasterMethodtoCreateHeap

• 📘Sorting Techniques

  • 01 Bubble Sort
  • 02 Insertionsort
  • 03 Selection Sort
  • 04 Mergesort
  • 05 Iterative Mergesort
  • 06 Nested recursion
  • 07 RecursiveMergeSort
  • 08 Count sort
  • 09 BinSort Based on LL
  • 10 RadixSort Using LL
  • 11 Shellsort

In software development we have two phases:-

• Design

• Implementation

• For designing any kind of software we should have a blueprint for that, i.e we can not develop any software on hit and trial basis.

• Algorithm:- Algorithm is step by step procedure do solve any kind of computational problem & It is the core of computer science.

• There is certain point about algorithm:-

• Algorithm is written at design time.

• For writing any effective one should have Proper domain Knowledge.

• Algorithm is language independent.

• And it is independent of Hardware & OS.

• We are doing priori analysis when writing algorithms.

• Mainly we are considering Time & Space function. Rather than that we are checking for Network Consumption/Data Transfer, Power consumption and Consumption of CPU Register.

• characteristics of Algorithm :-

• 1. Input
• 2. Output
• 3. Definiteness(Every Statement should be clear and understandable)
• 4. Finiteness(Algorithm must terminate at some time)
• 5. Effectiveness(Don’t write unnecessary steps)
• 6. Independent(It can be implemented in any programming language).

• 📘Time Complexity and Problems

• 📘Divide & Conquer

  • Merge Sort
  • Quick Sort
  • Binary Search (logn)
  • Closest Pair of Points | O(nlogn)
  • Strassen’s Matrix Multiplication
  • Maximul Subarray
  • Integer Multiplication
  • Karatsuba Algorithm for Fast Mul