Basics to Approches and Problem-Solving

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Full PlayList

Problem Count	Topic	Level	Problem	Solution	Notes	Time	R - 1	R - 2	R - 3
	Linked List
1	-	Easy	LeetCode	Reverse Linked List	updating notes...	❌
2	-	Medium	LeetCode	Add two numbers	updating notes...	❌
3	-	Medium	LeetCode	Remove Nth Node From End of List	updating notes...	❌

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Data Structures Implementation - `Videos`

• Nodes
• Linked List
  • Singly Linked List + All Operations
  • Doubly Linked List + All Operations
  • Circular Linked List
    • Circular Singly Linked List
      • Circular Singly Linked List + All Insertion Operations
      • Circular Singly Linked List + All Deletion Operations
    • Circular Doubly Linked List
      • Circular Doubly Linked List + All Insertion Operations
      • Circular Doubly Linked List + All Deletion Operations
• Array & List
• Stack
  • Array-based implementation
  • LinkedList-based implementation
• Queue
  • Array-based implementation
  • Linked list-based implementation
  • Circular queue
  • Priority queue
  • Deque (double-ended queue)
• Hash Tables
  • HashMap
  • HashSet
  • Collision resolution techniques (chaining, open addressing)
• Tree (Data Structures)
  • Tree Implementation
  • Binary Trees
    • Full binary tree
    • Complete binary tree
    • Perfect binary tree
  • Binary Search Trees (BST)
    • Balanced BST (e.g., AVL tree, Red-Black tree)
    • Splay tree
    • Treap
  • Heaps
    • Min-heap
    • Max-heap
    • Binary heap
    • Fibonacci heap
    • Binomial heap
  • Tries (Prefix Trees)
    • Standard trie
    • Compressed trie (Radix tree)
    • Suffix trie
  • Segment Trees
    • Standard segment tree
    • Lazy propagation
  • Fenwick Trees (Binary Indexed Trees)
    • Standard Fenwick tree
  • B-Trees
    • B-tree
    • B+ tree
    • B* tree
  • Quad Trees
    • Standard quad tree
  • K-D Trees
    • Standard K-D tree
  • Inorder
    • Recursive
    • Iterative
  • Preorder
    • Recursive
    • Iterative
  • PostOrder
    • Recursive
    • Iterative
• Graph Data Structures
  • Graphs
    • Adjacency matrix
    • Adjacency list
    • Edge list
  • Specialized Graphs
    • Directed graph (digraph)
    • Weighted graph
    • Undirected graph
    • Directed Acyclic Graph (DAG)

Advanced Data Structures

• Disjoint Set (Union-Find)
  • Quick-find
  • Quick-union
  • Union by rank
  • Path compression
• Bloom Filters
  • Standard Bloom filter
  • Counting Bloom filter
• Skip Lists
  • Standard skip list
• Suffix Arrays
  • Standard suffix array
• Sparse Tables
  • Standard sparse table

Specialized Data Structures

• Trie Variants
  • Patricia trie
  • Suffix tree
• Spatial Data Structures
  • R-tree
  • R*-tree
  • k-d tree
  • Quad tree
• Multidimensional Data Structures
  • Range tree
  • Interval tree
• Persistent Data Structures
  • Persistent array
  • Persistent list
  • Persistent tree

Click Here: (Data Structures Time & Space Complexity)

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Algorithms Implementation

• Sorting
  • Binary
  • Selection
  • Insertion
  • Quick
  • Merge
  • Counting
  • Radix
  • Bucket
  • Heap
• Search
  • Binary Search
  • Lower Bound
  • Upper Bound
  • Binary Search on Ranges
• String
  • Rabin Karp

Click Here: Algorithms Time & Space Complexity)

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Patterns & Hacks

Pattern 1: Given input is a sorted (array, list or matrix)
            Use a variation of:
                1. Binary Search or
                2. Two Pointer strategy

Pattern 2: If asked minimum/maximum/top/closest'k' elements among 'n' elements
            Use:
                1. Heap

Pattern 3: If required to try all Permutations or Combinations of a input
            Use either:
                1. Recursive _ Backtracking or
                2. Iterative _ Breadth-First Search

Pattern 4: If required to solve Trees or Graph problems
            Use either:
                1. Breadth-First Search or
                2. Depth-First Search

Pattern 5: If given a Set of Strings among that we have to find some Common Substring 
             Use either:
                1. HashMap or
                2. Trie

Hack 1: Try to convert Recursive Solution to Iterative Solution
            Use Stack

Hack 2: If given problem have a Brute-Force solution in O(n^2)Time and O(1)Space, Try to find out for other Two Solutions 
             Use either:
                1. Map or Set for O(n)Time and O(n)Space
                2. Sorting for O(n log n)Time and O(1)Space

Hack 3: If given problem is to Optimize something, (say Maximization or Minimization)
             Use:
                1. Dynamic Programming

Hack 4: If given Bunch of Strings and asked to search something 
             Use either:
                1. HashMap or
                2. Trie

Hack 5: If given problem is LinkedList one, and ExtraSpace is not allowed  
             Use:
                1. Fast & Slow Pointer approach

Coding Interview Patterns

Patterns

• Two Pointers
  • Fast and Slow Pointers
• In-place reversal of Linked List
• Sliding Window
• Island Matrix Traversal
• Merge Intervals
• Cyclic Sort
• Tree: Breadth First Search
• Tree: Depth First Search
• Two Heaps
• Subsets
• Modified Binary Search
• Bitwise XOR
• Top K Element
• K-way merge
• Backtracking
• 0-1 Knapsack (DP)
• Topological Sort (Graph)
• Multi-threaded

Dynamic Programming Patterns

Patterns

• Knapsack
• Unbounded Knapsack
• Fibonacci Numbers
• Palindromic Subsequence
• Longest Common Substring

System Design

Reference : List of Questions asked on System Design

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Study Approach

• Practice and Study consistently. No Streak breaks
• Create Flashcards daily.
  • Spend 1-2 hour synthesizing whatever you learn.
• List down all the aha moments in one file.
• Practice Java / Create Projects in JAVA
• Reserve time for writing notes and practicing flashcards

Tests

$ poetry install
$ poetry run pytest --benchmark-skip

If you don't use poetry, there is also a classic requirements.txt file. to be updated...

Bugs

If you find any bug or incorrect implementation in this repo, please let me know by opening an issue or pull request. Data community would appreciate your help since they provide some random strings which are used in two of test cases.

Also Refer

• Big-O Cheat Sheet
• Data Structure Visualizations
• Visualize Python Code Execution