Programs Completed.txt

[1] - Into to programming - 
1) Basic Into to programming and Fundamentals - Conditional & Looping Statement, Break & Continue, Functions, Pointers
2)  digit sum -
3) Reverse Number -
4) Prime no. -
5) Nested Loops  & Patterns - 
5.2) Star Pattern
5.3) Inverted Star Pattern
5.4) half Pyramid  Pattern
5.5) Character Pyramid Pattern
5.6) Hollow Rectangle Pattern
5.7) Inverted & Rotated Half Pyramid
5.8) Floyd's Triangle
5.9) Diamond Pattern
5.10) Butterfly Pattern
6) Number System - 
6.1) Binary to Decimal Conversion -
6.2) Decimal to Binary -
// -------------------


[2] - Arrays- 
1)Initiation Methods of an array and Output & input of an array -
2) Largest Value/Max Element in the array & 2.1) Min Element  -
3)  Dereferences of Pointer concept in Array -
4) Linear Search in array -
5) Reverse an array - 
5.1) using extra space
5.2 - W/o using Extra Space1 - 2 POINTERS APPROACH
6) Binary Search - It always for the Sorted Array
7) Array Pointer - 
7.1. Pointer Arithmetic Approaches -
7.2 - Addition & Subtraction of Constants -
7.3- Addition & Subtraction of Pointers 
7.4 - Comparison Operators 
8) Subarrays -
9) Max Subarray Sum -
9.1 - Clearly Brute Force Approach -
9.2 - Slightly Optimized approach - for decreasing the time complexity
9.3 - Using Most Optimized Approach - Kadane's Algorithms. For very less Time Complexity
10) buy & sell stock problem-
11) Trapping Rainwater Problem -
// -------------------


[3] - Sorting Algorithms - 
1) Bubble Sort Algo -
2) Selection Sort Implementation -
3) Insertion Sort Algorithm & Inbuilt Sorting technique - 
4) Counting Sort
// -------------------


[4] - Matrix in CPP – 
1) 2D Array Basic Introduction & Input, Output
2) Spiral matrix -
3) Diagonal Sum of Matrix -
4) Search for targeted element in Sorted Matrix -
4.1) - Brute Force Approach - most simple method. T.C - O(n*m)
4.2) - Using Binary Search - 2nd Optimum - Row Wise - O(n*logn), Colm Wise - O(m*logn)
4.3) - Staircase Search technique - O(n+m)
// -------------------


[5] - Character Array & Strings in CPP – 
1) Intro to Char Array – 
2) Covert to Upper Letter -
3) Reverse a Char Array -
4) Valid Palindrome in char array -
5) Char Array(String) Functions -
6)String Intro & Basic I/p, o/p operations - 6.1) String Member Functions-
7) Check the two strings are Anagram or not -
// -------------------


[6] - STL - Vector
1) Pair_Sum - FInd if any pair in Sorted Array has target sum
1.1) Brute Forece Approach - using Nested Loops. TC - O(n^2)
1.3) Uisng Linear Approach - 2 Pointer Approach. TC - O(n)
// -------------------


[7] Bit Manipulations – 
1)Bitwise Operators  -
2) Check if even or odd -
3) Get ith Bit of a num - 
4) Set ith Bit - (sets the value to 1) - 
5)Clr ith Bit - (sets the value to 0)
6) No. is power of 2 -
7) Count of Set Bits -
8) Fast Exponentiation -
// -------------------


[8] OOP’s in CPP – 
1) Classes & Object basic Intro -
1.1) Access Modifiers
1.2) Getters & Setters -
2) Encapsulations -
2.1) This Constrcutor
2.2) Types of Cosntrcutrs -
2.3) Copy Constructor Conceppt -
2.4) Shallo & Deep Copy -
3) Destructor - 
4) Inheritance -
4.1) Mode of Inharitance - 
4.2) types of Inheritance -
4.2.1) Single Inheritance -
4.2.2) Multi-Level Inheritance -
4.2.3) Multiple Inheritance -
4.2.4) Hierarchical Inheritance -
4.2.5) Hybrid Inheroitance -
5) Polymorphism -
5.1) Compiletime Polymorphism - 
5.1.1) Function Overloading  -
5.1.2) Function Overloading  -
5.2)Polymorphism -
5.2.1)Function Overriding  -
5.2.2)Virtual Functions -
6) Abstraction -
7) Static Keyword -
8) Friend Class & Friend Function - 
// -------------------




[9] Recursion – 
1)Recursion Basic Understanding-
2)Recursion QUns - 
2.1) Print the numbers in descending  Order
2.2) Stack Overflow -
2.3)Sum of N-Natural Nmbers -
2.4) Print Nth Fibonacci Number -
2.5) Check if Array is Sorted or Not -
2.6) First OCcurence -
2.6.1) Last OCcurence -
2.7) X to the power N  -
3) Tiling problem
4) Remove Duplicates from the String -
5) Friends Pairing Problem -
6) Binary String Problm -
// -------------------


[10] Divide & Conquer – 
1) Merge Sort Algo -
2) Quick Sort Algorithm -
2.1) Quick Sort Worst Case Scenario - 
3) Searching In Rotated Array Problem  - 
// -------------------


[12] Backtracking  - 
1) Backtracking In Arrays -
2) Find Subsets/Substrings -
3) Find Permutations -
4) N_Quee problem -
5) GridWays Problem - 
6) SudokuSOlver - 
// -------------------


[13] Greedy Algorithms 
1) Activity Selection Problem  -
2) Pair in C++ : STL container to store 2 objects - 
3) Fractional Knapsack Problem -
4) Minimum Absolute DIfferent Pairs -
5) Maximum Chain Length of Pairs -
6) Indian Coins Problem -
7) Job Sequencing Problem -
// -------------------

[14] Linked List – 
1) Linked List Introduction & Creation -
1.2) Deletion in LL -
2) Iterative Search in LL -
2.2) Recursive Search in LL -
3) Reverse a LinkedList -
4) Find & Remove Nth Node from LL -
5) Floyd's Cycle FInding Algorithm - Detect a Cycle/Loop in LL
5.1) Remove a cycle from LL -
6) LL using STL in CPP -
7) Merge Sort Implemetation on Linked List -
8) Zig-Zag LL - Alternate Nodes in LL - 
9) DoublyLinkedList Concept - 
// -------------------

[15] Stack - 
1) Stack Implementation using Vector -
1.1) Stack implemtation for any type of Datatype
2) Stack impmentation usig LL -
Case 1 - using STL LL -
Case 2 - By creating LL manually -
3) Stack in STL -
4) Push at Bottom of the Stack -
5) Reverse a string using stack -
6) Reverse a  stack using recursion -
7) Stock Spain Problem -
8) Next Greater Element  -
9) Valid Paranthesis Problem -
10) Duplicate  Paranthesis Problem -
11) Max Area in the Histogram  -
// -------------------

[16] Queue  - 
1) Queue Implementation using LL: -
2) STL Queue Functionality -
3) Queue using 2 stacks -
3.1) Stack using 2 Queues -
4) First Non-Repeating Letter -
5) Interleave of 2 Queues -
6) Reverse a Queue -
7) Deque[Double Ended Queue] concept in Queue -
7.1)  Queue using Deque -
7.2) Stack using Deque -
8) Circular Queue Implementations using Array -
// -------------------


[17] Binary Tree – 
0) Intro to Binary Search - 
1) Creating Binary Tree through Pre Ordder Traversal -
2) Tree Traversal techniques -
2.1) Pre Order Traversal -
2.2) IN Order Traversal-
2.3) Post Order Traversal-
2.4) Level Order Traversal -
2.4.1) - Modification in Level Order Traversal - Pushing all elements Level Wise in Output
3) Height of a Tree -
4) Count of Nodes in a Tree -
5) Sum of Nodes in a Tree -
6) Check from Root to asked Node if the path exist or not ?
7) Diameter of a tree - inn O(N^2)
7.1) Diameter of a tree - in O(N)
8) Subtree of ANother Tree -
9) Map in Cpp -
10) Top view of a Tree -
11) Bottom view of a Tree - 
12) Kth Level of a Tree -
12.1 - using Iterative Level Order Method -
12.2) - Using Rrecursion - recurively searching approach for kth level
13) Lowest Common Ancestor - using fundamental approach - where TC - O(n) & Sc- O(n)
13.1) - Optimized appraoch fro SC - O(1)
14) Min. Distance between Nodes -
15) Kth Ancestor of Node -
16) Transform to Sum Tree -
// -------------------

[18] Binary Search Tree - 
0) Intro to BST
1) Build BST from nodes -
2) Search in a BST -
3) Deletion of a Node in BST -
4) Print in a Range -
5) Root to leaf Path -
6) Validate BST -
7) Sorted nodes to Balanced BST -
8) Convert BSt to Balanced BST -
9) Size of Largest BSt in BT -
10) Merge  2 BST's -
// -------------------

[19] Priority Queue & Heap 
1) Priority Queue Introduction - 
2) Complete Binary Tree - 
2.1) Heap Data Structure Max/Min-  
2.1.1) Implementation of Max Heap - 
2.1.2) Implementation of Max Heap - 
3) Priority Queue For Pair/Objects -
3.1) Priority_Queue for Objects - 
3.2) Using Priority Queue for Creating Pairs -
4) Heap Sort & its implemetations - 
5) Quns Based on Priority_Queue and Heap - 
5.1) Nearby K Cars -
5.2) Connect N Ropes -
5.3) Weakest Soldier -
5.4) Sliding Window Maximum -
// -------------------

[20] Hashing – 
1) Hashmap Data Structures using Hash Table Implementation -  
2) STL COntainersMap - Unordered Map & Map - 
2.1) Unordered Map Working -
2.2) Map Working -
3) STL COntainersMap - Unordered Set & Set - 
3.1) Unorderd Set Working -
3.2) Set Working -
4) Quns using STL Containers  - 
4.1) Pair Sum/Two SUm/Target Sum -
4.2) Majority Element  -
4.3) Valid Anagram -
4.4) Count Distinct -
4.5) Union & Interesection -
4.6) itinerary From Tickets -
4.7) Largest Subarray with sum 0 -
4.8) Count of Subarray sum Equals to K -
// -------------------

[21] Trie 
1) Trie Intro  -
2) Trie Quns -
2.1) Word Break Problem -
2.2) Prefix Problem -
2.3) StartWithProblem -
2.4) COunt Unique Substring -
2.5) Longest Word with all Prefix  -
// -------------------

[22] Segment Trees – 
1) Intro to Segment Trees : - 
1.1) Creating a Segment Tree - 
2) Performing QUeries in Segment Trees  -
3) Update on any index in Segment Tree -
4) Max Segment Tree - in particular given range - 
4.1) Creation & Query in Max Segment Tree - 
4.2) Update in Range Max Segment Tree - in particular given range - 
5) Range Min Segment Tree - Creation, Query & Update in particular given range - 
// -------------------

[23] Graph - 
0) Intro to Graph, Types of Graph & Methods for stroing a Graph – 
1) Graph Creation -
2) Graph Traversal Techniques -
2.1) BFS Implementation on Graph -
2.2) DFS Implementation on Graph -
3) HasPath Problem -
3.1) Using DFS -
4) Diconneted Graph OR Disconnected Components -
4.1) using DFS Traversal -
4.2) using BFS Traversal -
5) Cycles in Graph -
5.1) Cycle Detection in an Undirected Graph - using DFS - 
5.1.1) Cycle Detection in  Directed Graph - using DFS - 
6) Bipartite Gtaph -
7) All PAth Problem -
8) Topological Sorting -
8.1) Leetcode 207) Course Schedule Problem -
8.2) Leetcode 210) Course Schedule II -
9) Kahn's Algorithm (using BFS) -
9.1) Kahn's Algorithm For getting Cycles in Graph -
10) Dijkstra's ALgorithms -
11) Bellman Ford Algorithm -
12) Minimum SPanning Tree(MST) -
12.1) Prim's Algorithm -
12.2) - Leetcode 1584 - Min Cost to Connect All Points
13) Leetcode Qun 787 - Cheapest Flight Within K Stops -
14) Disjoint Set/UnionFind Data Structure -
15) Kruskal's ALgorithms -
16) Flood Fill ALgorithms - Leetcode Qun - 733 -
// -------------------

[24] Dynamic Programming OR Optimized Recursion Programming -
1) Overview for DP -, What is DP & When to use it -, Types of using DP - 
2) DP Patterns using QUns -
2.1) Pattern - I : Fibonacci Pattern
2.1.1) CLimbing Stairs Problem - 
Using Recurison Only - 
Now using the DP using MEMOIZATION -
Now using the DP using TABULATION -
2.1.2) CLimbing Stairs Problem Variaation - When 3 jumps are allowed
2.2) Pattern - II : Knapsack Problem Pattern
2.2.1) - 0-1 Knapsack Problem - Using Recursion,  0-1 Knapsack Problem DP(using Memoization), 0-1 Knapsack Problem DP(using Tabulaiton) -
2.2.2) - Target Sum Subset - Tabulaiton Approach - 
2.2.3) Minimum Partitioning - Using Tabulation Approach -
2.3) Pattern - III : Unbounded Knapsack -
2.3.1 -  Leetcode 518 - Coin Change - II Coin Change Problem - Using Tabulation -
2.3.2 - ROd Cuttitng Problem - Using Tabulation Approach - 
2.3.3 - Leetcode 1547 - Min cost to cut sticks
2.4) Pattern - IV : Longest Common Subsequence Problem Pattern -, Using Recursion, - Using Memoization, -Using Tabulation -
2.4.2) -Longest Common SUbstring -, Using Tabulation only -
2.4.3) -Longest Increasing Subsequence -
2.4.4) - Leetcode - 72) Edit Distance - using Tabulation Approach
2.4.5) - Leetcode - 44)  WildCard Matching Problem - using Tabulation Approach - 
2.5) Pattern - V : Catalan's Number -, 2.5.1) Catan's Number using Recursion -, Catan's Number using Memoization -, Catan's Number using Tabulation -
2.5.2) - Leetcodee - 96) Count BST's - FInd coutn of all possible structurally unique BSTs that can be forned with n nodes - using Tabulatoin -
2.5.3) - Mountain Ranges Problem -
2.6) Pattern - VI : Matric Chain Multiplication(MCM)
2.6.1) using  Recursion -, using Memoization -, using Tabulation -
// -------------------