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Top 10 Algorithms in Interview Questions

Last Updated : 15 Jan, 2024
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Getting ready for a tech job interview? Algorithms are really important! Companies often ask questions that require problem-solving skills. In this article, we’ll look at the top 10 algorithms that are commonly used in interviews. Each algorithm is like a powerful tool in your problem-solving toolbox. Knowing them well can really help you handle different technical challenges during interviews. Let’s break down these important algorithms to make your interview preparation more effective. If you’re getting ready for a coding interview, it’s essential to go through these problems.

1. Array Algorithm

Maximum Subarray Sum
Find the Missing Number
Trapping Rain Water
Maximum Product Subarray
Find the equilibrium index of an array
Leaders in an array
Minimum Platforms Required for a Railway/Bus Station
Rotate an array to the right by k steps
Kth smallest/largest element in an array
Maximum Length Bitonic Subarray

2. String Algorithm

Longest Palindromic Substring
String Matching with Wildcard
Edit Distance
Longest Repeating Subsequence
Count all distinct substrings of a given string
Reverse words in a given string
Check if a string is a rotated palindrome
KMP Algorithm for Pattern Searching
Minimum characters to be added at front to make string palindrome

3. Sorting Algorithm

Counting Sort
Radix Sort
Bubble Sort
Selection Sort
Insertion Sort
Shell Sort
Bucket Sort

4. Searching Algorithm


Linear Search

Binary Search

Ternary Search

Depth-First Search (DFS)
Breadth-First Search (BFS)
Fibonacci Search

5. Recursion/Backtracking Algorithm

N-Queens Problem
Sudoku Solver
Rat in a Maze
Word Break Problem using Backtracking
Subset Sum Problem
Permutations of a given string
Combination Sum
Generate all possible valid IP addresses from given string
Rat in a Maze with multiple steps or jump allowed

6. Greedy Algorithm

Fractional Knapsack
Huffman Coding
Job Sequencing with Deadlines
Activity Selection Problem
Greedy Algorithm to find Minimum number of Coins
Minimum Number of Platforms Required for a Railway/Bus Station
Maximum Length Chain of Pairs
Minimize Cash Flow among a given set of friends who have borrowed money from each other
Connect n Ropes with Minimum Cost
Prim’s Minimum Spanning Tree (MST)

7. Tree Algorithm

Lowest Common Ancestor (LCA)
Diameter of Binary Tree
Binary Tree Level Order Traversal
Serialize and Deserialize a Binary Tree
Check if a Binary Tree is BST
Inorder Traversal without Recursion
Convert Binary Tree to Doubly Linked List
Check if Two Trees are Identical
Maximum Width of a Binary Tree
Mirror of a Binary Tree

8. Dynamic Programming Algorithm

Longest Common Subsequence
0/1 Knapsack
Matrix Chain Multiplication
Longest Increasing Subsequence
Maximum Sum Increasing Subsequence
Coin Change Problem
Longest Palindromic Subsequence
Edit Distance
Largest Sum Contiguous Subarray
Longest Common Substring

9. Graph Algorithm

Dijkstra’s Algorithm
Kruskal’s Algorithm
Topological Sorting
Bellman-Ford Algorithm
Floyd Warshall Algorithm
Prim’s Algorithm
Depth-First Traversal of a Graph
Breadth-First Traversal of a Graph
Detect Cycle in a Directed Graph
Articulation Points (or Cut Vertices) in a Graph

10. Bit Manipulation Algorithm

Find the Only Non-Repeating Element
Count Total Set Bits
Maximum XOR of Two Numbers in an Array
Find the two non-repeating elements in an array of repeating elements
Check if a number is sparse or not
Count total set bits in all numbers from 1 to n
Maximum subarray XOR in a given array
Sum of XOR of all subarrays
Find the element that appears once in an array where every other element appears twice
Program to find whether a no is power of two

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