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

Stack

Here are some common approaches that can be used with the stack data structure:

  1. Iterative Approach: This involves looping over the data and using a stack to keep track of elements. For example, you might use an iterative approach with a stack to traverse a tree or graph, convert an infix expression to postfix, or check for balanced parentheses in an expression.

  2. Recursive Approach: Although not exactly the same as iteration, recursion is a related concept that often goes hand-in-hand with stacks. Recursion involves a function calling itself with modified arguments until a base case is reached. The call stack, which is an actual stack data structure, keeps track of these recursive calls.

  3. Dynamic Programming: Stacks can be used in certain dynamic programming problems where the optimal solution can be found by making optimal choices at each step. For example, the largest rectangular area under a histogram can be found using a stack in a dynamic programming approach.

  4. Memoization: Similar to dynamic programming, memoization involves storing the results of expensive function calls and reusing them when the same inputs occur again. While memoization is typically used with recursion, it can also be used with stacks in certain contexts.

  5. Divide and Conquer: Stacks can be used in a divide-and-conquer approach where a problem is divided into smaller subproblems that are solved independently. The classic Tower of Hanoi problem can be solved using a divide-and-conquer approach with three stacks.

Remember, the choice of approach depends on the specific problem at hand. Understanding the problem and the data structure is key to choosing the most efficient approach.

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Last updated 1 year ago