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Top 20 most asked DSA questions to ace your next interview:
➤ Arrays and Strings:
1. Find the maximum sum subarray.
2. Implement the "two sum" problem.
3. Implement Kadane's algorithm for maximum subarray sum.
4. Find the missing number in an array of integers.
5. Merge two sorted arrays into one sorted array.
6. Check if a string is a palindrome.
➤ Linked Lists:
7. Reverse a linked list.
8. Detect a cycle in a linked list.
9. Find the middle of a linked list.
10. Merge two sorted linked lists.
➤ Stacks and Queues:
11. Implement a stack that supports push, pop, top, and retrieving the minimum element.
12. Implement a circular queue.
13. Design a queue using stacks.
➤ Trees and Binary Search Trees:
14. Find the height of a binary tree.
15. Validate if a binary tree is a valid binary search tree.
16. Implement an inorder traversal of a binary tree.
➤ Graphs:
17. Implement depth-first search (DFS).
18. Find the shortest path between two nodes in an unweighted graph.
➤ Sorting and Searching:
19. Implement quicksort.
20. Implement binary search.
Best DSA Resources: 👇
https://topmate.io/coding/886874
All the best 👍👍
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Essential 22 DSA patterns for coding interviews 👇👇
1. Fast and Slow Pointer
- Cycle detection method
- O(1) space efficiency
- Linked list problems
2. Merge Intervals
- Sort and merge
- O(n log n) complexity
- Overlapping interval handling
3. Sliding Window
- Fixed/variable window
- O(n) time optimization
- Subarray/substring problems
4. Islands (Matrix Traversal)
- DFS/BFS traversal
- Connected component detection
- 2D grid problems
5. Two Pointers
- Dual pointer strategy
- Linear time complexity
- Array/list problems
6. Cyclic Sort
- Sorting in cycles
- O(n) time complexity
- Constant space usage
7. In-place Reversal of Linked List
- Reverse without extra space
- O(n) time efficiency
- Pointer manipulation technique
8. Breadth First Search
- Level-by-level traversal
- Uses queue structure
- Shortest path problems
9. Depth First Search
- Recursive/backtracking approach
- Uses stack (or recursion)
- Tree/graph traversal
10. Two Heaps
- Max and min heaps
- Median tracking efficiently
- O(log n) insertions
11. Subsets
- Generate all subsets
- Recursive or iterative
- Backtracking or bitmasking
12. Modified Binary Search
- Search in variations
- O(log n) time
- Rotated/specialized arrays
13. Bitwise XOR
- Toggle bits operation
- O(1) space complexity
- Efficient for pairing
14. Top 'K' elements
- Use heap/quickselect
- O(n log k) time
- Efficient selection problem
15. K-way Merge
- Merge sorted lists
- Min-heap based approach
- O(n log k) complexity
16. 0/1 Knapsack (Dynamic Programming)
- Choose or skip items
- O(n * W) complexity
- Maximize value selection
17. Unbounded Knapsack (Dynamic Programming)
- Unlimited item choices
- O(n * W) complexity
- Multiple item selection
18. Topological Sort (Graphs)
- Directed acyclic graph
- Order dependency resolution
- Uses DFS or BFS
19. Monotonic Stack
- Maintain increasing/decreasing stack
- Optimized for range queries
- O(n) time complexity
20. Backtracking
- Recursive decision-making
- Explore all possibilities
- Pruning with constraints
21. Union Find
- Track and merge connected components
- Used for disjoint sets
- Great for network connectivity
22. Greedy Algorithm
- Make locally optimal choices
- Efficient for problems with optimal substructure
- Covers tasks like activity selection, minimum coins
Best DSA Resources: 👇
https://topmate.io/coding/886874
All the best 👍👍
1 096
Complete DSA Roadmap
|-- Basic_Data_Structures
| |-- Arrays
| |-- Strings
| |-- Linked_Lists
| |-- Stacks
| └─ Queues
|
|-- Advanced_Data_Structures
| |-- Trees
| | |-- Binary_Trees
| | |-- Binary_Search_Trees
| | |-- AVL_Trees
| | └─ B-Trees
| |
| |-- Graphs
| | |-- Graph_Representation
| | | |- Adjacency_Matrix
| | | └ Adjacency_List
| | |
| | |-- Depth-First_Search
| | |-- Breadth-First_Search
| | |-- Shortest_Path_Algorithms
| | | |- Dijkstra's_Algorithm
| | | └ Bellman-Ford_Algorithm
| | |
| | └─ Minimum_Spanning_Tree
| | |- Prim's_Algorithm
| | └ Kruskal's_Algorithm
| |
| |-- Heaps
| | |-- Min_Heap
| | |-- Max_Heap
| | └─ Heap_Sort
| |
| |-- Hash_Tables
| |-- Disjoint_Set_Union
| |-- Trie
| |-- Segment_Tree
| └─ Fenwick_Tree
|
|-- Algorithmic_Paradigms
| |-- Brute_Force
| |-- Divide_and_Conquer
| |-- Greedy_Algorithms
| |-- Dynamic_Programming
| |-- Backtracking
| |-- Sliding_Window_Technique
| |-- Two_Pointer_Technique
| └─ Divide_and_Conquer_Optimization
| |-- Merge_Sort_Tree
| └─ Persistent_Segment_Tree
|
|-- Searching_Algorithms
| |-- Linear_Search
| |-- Binary_Search
| |-- Depth-First_Search
| └─ Breadth-First_Search
|
|-- Sorting_Algorithms
| |-- Bubble_Sort
| |-- Selection_Sort
| |-- Insertion_Sort
| |-- Merge_Sort
| |-- Quick_Sort
| └─ Heap_Sort
|
|-- Graph_Algorithms
| |-- Depth-First_Search
| |-- Breadth-First_Search
| |-- Topological_Sort
| |-- Strongly_Connected_Components
| └─ Articulation_Points_and_Bridges
|
|-- Dynamic_Programming
| |-- Introduction_to_DP
| |-- Fibonacci_Series_using_DP
| |-- Longest_Common_Subsequence
| |-- Longest_Increasing_Subsequence
| |-- Knapsack_Problem
| |-- Matrix_Chain_Multiplication
| └─ Dynamic_Programming_on_Trees
|
|-- Mathematical_and_Bit_Manipulation_Algorithms
| |-- Prime_Numbers_and_Sieve_of_Eratosthenes
| |-- Greatest_Common_Divisor
| |-- Least_Common_Multiple
| |-- Modular_Arithmetic
| └─ Bit_Manipulation_Tricks
|
|-- Advanced_Topics
| |-- Trie-based_Algorithms
| | |-- Auto-completion
| | └─ Spell_Checker
| |
| |-- Suffix_Trees_and_Arrays
| |-- Computational_Geometry
| |-- Number_Theory
| | |-- Euler's_Totient_Function
| | └─ Mobius_Function
| |
| └─ String_Algorithms
| |-- KMP_Algorithm
| └─ Rabin-Karp_Algorithm
|
|-- OnlinePlatforms
| |-- LeetCode
| |-- HackerRank
Best DSA RESOURCES: https://topmate.io/coding/886874
Credits: https://t.me/free4unow_backup
All the best 👍👍
