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Basic Algorithms

Problem	Solution with time and space complexity	Resources
DFS	Solution Time Complexity Space Complexity Graph DFS O(n) O(n) To keep track of visited nodes Graph and Tree DFS O(n) O(n) To keep track of visited nodes	YouTube Video
BFS	Solution Time Complexity Space Complexity Graph BFS O(n) O(n) To keep track of visited nodes Graph and Tree BFS O(n) O(n) To keep track of visited nodes	YouTube Video
Topological Sort	Solution Time Complexity Space Complexity TopologicalSort.py Topological Sort.py Topological Sort DFS.py Topological Sort Using Matrix Graph.py O(MN^2) Total number of nodes	The provided approaches only work if the graph is directed and acyclic. YouTube Video
Heap Sort	Solution Time Complexity Space Complexity	Part 1 - The Structure of Heap , How to Add an Item Part 2 - How to Remove an Item from a Heap Part 3 - Describing a Heap as an Array

Arrays

Problem	Solution with time and space complexity	Resources
Two Sum	Solution Time Complexity Space Complexity One pass HashTable O(n) O(n) Two pass HashTable and Two Pointers approach HashTable Approach: O(2n) Two Pointer: O(n log n) HashTable Approach: O(n) Two Pointer: O(1)	Resources
Group Anagrams	Solution Time Complexity Space Complexity Pt1 Pt2 Sorting and character counting approach Sorting: O(KN log N) Character Counting: O(KN) K = total words N = length of longest word Sorting: O(K) Character Counting: O(K)	Resources
Merge Sorted Arrays	Solution Time Complexity Space Complexity Merge Sorted Arrays.py O(n) Length of first Array + Length of second array
Remove Element	Solution Time Complexity Space Complexity Remove Element Pt1.py O(n) O(1) Remove Element Pt2.py O(n) O(1)
Contains Duplicate	Solution Time Complexity Space Complexity Pt1 Pt2 HashTable Approach: O(n) Sorting Approach: O(n log n) Hash Approach: O(n) Sorting Approach: O(1)	Resources
Valid Anagram	Solution Time Complexity Space Complexity Pt1 Pt2 Sorting approach: O(n log n) HashTable approach: O(n) Sorting approach: O(n) HashTable approach: O(26)	Resources
Top K Frequent Elements	Solution Time Complexity Space Complexity Heap approach Heap approach pt2	Resources
Product of Array Except Self	Solution Time Complexity Space Complexity Solution link Solution link O(3n) O(2n)	Resources
Pascal's Triangle	Solution Time Complexity Space Complexity Pt1 Pt2 Pt3 O(n) O(n)	Resources
Pascal's Triangle II	Solution Time Complexity Space Complexity Pt1 Pt2 Exponential O(n)	Resources

Backtracking

Problem	Solution with time and space complexity	Resources
Generate all permutations of a string	Solution Time Complexity Space Complexity Python Solutions Factorial Time Number of Unique characters in the string X Total number of characters in the string Python Solution Pt2 Factorial Time Number of Unique characters in the string X Total number of characters in the string	YouTube Video
Given an array with unique elements, generate all sub arrays from that array	Solution Time Complexity Space Complexity Array Permutations.py Exponential O(n)
Word Search	Solution Time Complexity Space Complexity Word Search.py Word Search Speed Coding.py Word Search Pt2.py O(MN) O(MN) when we get next moves	Don't forget to mark cells visited
Word Search II	Solution Time Complexity Space Complexity Word Search II.py Word Search II pt2.py Word Search II Pt3.py O(total number of words X MN) Total number of words Word Search II Speed Coding.py	Use Tries if you want to reduce the time complexity
Vowels of All Substrings	Solution Time Complexity Space Complexity Solution link O(n^2) O(1)

Graph

• What are some ways of representing graph in code ?

  • Matrix

  	A	B	C
  A	0	1	0
  B	0	0	1
  C	1	0	0

  • Adjacency List
    Using Hash Map: {
    A:B,
    B:C,
    C:A }
    Visit here to understand better
  • Linked List
  

Problem	Solution with time and space complexity	Resources
Course Schedule	Solution Time Complexity Space Complexity Using graph represented as matrix O(n^2) O(n^2) Where n is number of courses Solution link	Use Topological Sorting

Hash Table

Problem	Solution with time and space complexity	Resources
Logger Rate Limiter	Solution Time Complexity Space Complexity Logger Rate Limiter.py O(1) O(n) n is number of messages
Subdomain Visit Count	Solution Time Complexity Space Complexity Speed coding Midnight Coding O(total domains * total subdomains) O(n)	Resources

Intervals

Problem	Solution with time and space complexity	Resources
Minimum Number of Taps to Open to Water a Garden	Solution Time Complexity Space Complexity Recursive approach Exponential O(n)	Resources
Minimum number of intervals to cover the target interval	Solution Time Complexity Space Complexity Minimum number of intervals.py O(n log n) O(1)	Resources
Meeting Rooms II	Solution Time Complexity Space Complexity Pt1 Pt2 Pt3 O(n log n) O(n/2)	Use Min Heap

Math

Problem	Solution with time and space complexity	Resources
Print all prime factors of a number	Solution Time Complexity Space Complexity Print All Prime Factors.py O(sqrt(n)) O(1)	Resources

Matrix

Problem	Solution with time and space complexity	Resources
Valid Sudoku	Solution Time Complexity Space Complexity Valid Sudoku.Py O(n^3) O(1) Valid Sudoku Pt2.Py O(n^3) O(n)
Number of Islands	Solution Time Complexity Space Complexity Number Of Islands.py Number of Islands (LeetCode Accepted).py Number of Islands pt3.py Number of Islands pt4.py Number of Islands Pt5.py O(mn* number of islands) ~= O(mn) O(1)	Resources
Max Area of Island	Solution Time Complexity Space Complexity Max Area of Island.py Time complexity Space complexity Max Area of Island pt2.py Time complexity Space complexity Max Area of Island Pt3.py O(mn) O(1)	Resources

Sorting

Problem	Solution with time and space complexity	Resources
Rank Teams by Votes	Solution Time Complexity Space Complexity Solution link O(n) O(n)	Took help of chatGPT and algo monster

Stack

Problem	Solution with time and space complexity	Resources
Minimum Remove to Make Valid Parentheses	Solution Time Complexity Space Complexity Minimum Remove to Make Valid Parentheses.py Minimum Remove to Make Valid Parentheses pt2.py Minimum Remove to Make Valid Parentheses Pt3.py O(n) O(n)	Resources

Tree

Problem	Solution with time and space complexity	Resources
Maximum Average Subtree	Solution Time Complexity Space Complexity Maximum Average Subtree.py Traverses the whole tree once O(1)	Resources
Serialize and Deserialize N-ary Tree	Solution Time Complexity Space Complexity Pt1 Pt2 Pt3 Serialize: O(n) Deserialize: O(n) Serialize: O(2n) at max Deserialize:O(n)	Geeks for Geeks
Construct Binary Tree from Preorder and Inorder Traversal	Solution Time Complexity Space Complexity Solution link O(n) O(n) If you count tree nodes	Resources

Trie

Problem	Solution with time and space complexity	Resources
Implement Trie (Prefix Tree)	Solution Time Complexity Space Complexity Trie.py Trie using Hash Map Trie Pt2 O(word length) O(word length)	Leetcode editorial

Two Pointers

Problem	Solution with time and space complexity	Resources
Valid Palindrome	Solution Time Complexity Space Complexity Valid Palindrome Pt2 O(n/2) O(1)
Is Subsequence	Solution Time Complexity Space Complexity Is Subsequence.py O(long string) O(1)