Data Structure & Algorithms
  • 🖌️Unlocking the Power of Algorithms with C#
  • Data Structure
    • Data Structure
    • Big O
    • Array
    • Linked Lists
    • Stacks
    • Queues
    • Hash Tables
    • Trees
    • Graphs
    • Heap Sort
    • ParkingLot Algorithm
    • LRU cache
    • Priority Queue
  • Algorithms
    • Algorithm
    • Recursion
    • Sorting
    • Searching
    • Dynamic Programming
  • Problems
    • Array
      • Two Sum
      • Two Sum II - Input Array Is Sorted
      • Contains Duplicate
      • Maximum Subarray
      • House Robber
      • Move Zeroes
      • Rotate Array
      • Plus One
      • Find number of subarrays with even length
      • Find number of subarrays with even sum
      • Find Missing Element
      • Reduce Array Size to The Half
      • Remove Duplicates
      • Merge Sorted Arrays
      • Arrays Intersection
      • 3Sum
      • Trapping Rain Water
      • Maximum sum of a subarray
      • Longest Subarray
      • Subarray Sum Equals K
      • Container With Most Water
      • Missing Number
      • Roman to Integer
      • First Missing Positive
      • Unique Integers That Sum Up To 0
      • Integer to Roman
      • Flatten
    • String
      • Check if two strings are permutation of each other
      • String Compression
      • Palindrome Permutation
      • Determine if a string has all Unique Characters
      • One Away
      • Longest Substring Without Repeating Characters
      • Valid Palindrome
      • Valid Palindrome II
      • Backspace String Compare
      • First Unique Character in a String
      • Is Subsequence
      • URLify a given string
      • String has same characters at same position
      • Number of Ways to Split a String
      • Check whether two Strings are anagram of each other
      • Print last `n` lines of a big file or big string.
      • Multiply Strings
    • Matrix
      • Search a 2D Matrix
      • Search a 2D Matrix II
      • Rotate Matrix
      • Spiral Matrix
      • Set Matrix Zeroes
    • Bit Manipulation
      • Sum of Two Integers
      • Reverse Number
      • Reverse Number II
      • Binary Bits Count
      • Binary Bits Count II
    • Stack
      • Valid Parentheses
      • Balance or not expression
      • Decode String
    • Tree
      • Binary Tree Inorder Traversal
      • Binary Tree Preorder Traversal
      • Binary Tree Postorder Traversal
      • Binary Tree Level Order Traversal
      • Binary Tree Return All Root-To-Leaf Paths
      • Binary Tree Height-Balanced
      • Valid Binary Search Tree
      • Binary Tree Sum of all left leaves.
    • Linked List
      • Linked List Delete Middle Node
      • Merge Sorted Linked List
      • Reverse Linked List
      • Remove Duplicates from Sorted List
      • Remove Duplicates from Unsorted List
      • Linked List Cycle
    • Graph
      • The Number Of Islands
      • Number of Closed Islands
      • Max Area of Island
      • Rotting Oranges
      • Number of Provinces
      • Course Schedule
      • Surrounded Regions
      • Snakes and Ladders
      • Widest Path Without Trees
      • Knight Probability in Chessboard
      • Possible moves of knight
      • Check Knight Tour Configuration
      • Steps by Knight
      • Network Delay Time
    • Greedy
      • Best Time to Buy and Sell Stock
      • Best Time to Buy and Sell Stock II
      • Smallest Subset Array
      • Jump Game
    • Backtracking
      • Towers of Hanoi
      • Subsets
      • Combination Sum
      • Sudoku Solver
      • Word Search
    • Heap
      • Kth Largest Element in an Array
      • Top K Frequent Elements
    • Sorting
      • Order Colors String
    • Recursion
      • Number To Text
      • Divide Number
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  1. Problems

Graph

Here are some common approaches that can be used to solve problems related to graphs in data structures and algorithms:

  1. Depth-First Search (DFS): This is a traversal method used to explore all the nodes of a graph as far as possible along each branch before backtracking.

  2. Breadth-First Search (BFS): Also known as level-order traversal, this method visits all the nodes of a graph (or tree) at the current depth (or level) before going to the next depth.

  3. Dijkstra’s Algorithm: This is a greedy algorithm used for finding the shortest paths from a single source vertex to all other vertices in a graph with non-negative edge weights.

  4. Bellman-Ford Algorithm: This is used for finding the shortest paths from a single source vertex to all other vertices in a graph. Unlike Dijkstra’s algorithm, Bellman-Ford can handle graphs with negative edge weights.

  5. Floyd-Warshall Algorithm: This is a dynamic programming algorithm used for finding the shortest paths between all pairs of vertices in a graph.

  6. Prim’s Algorithm: This is a greedy algorithm used for finding a minimum spanning tree for a weighted undirected graph.

  7. Kruskal’s Algorithm: This is another greedy algorithm used for finding a minimum spanning tree in a graph.

  8. Topological Sort: This is used for directed acyclic graphs and is useful for scheduling tasks.

  9. Union-Find: This is a data structure that keeps track of a partition of a set into disjoint subsets. It’s used in Kruskal’s algorithm for minimum spanning tree.

  10. A Search Algorithm: This is an informed search algorithm, or a best-first search, meaning that it is formulated in terms of weighted graphs: starting from a specific starting node of a graph, it aims to find a path to the given goal node having the smallest cost (least distance travelled, shortest time, etc.).

Remember, the best approach to use depends on the specific problem you’re trying to solve. It’s always a good idea to understand the problem thoroughly and consider different approaches before deciding on the best one.

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Last updated 1 year ago