Clear all DSA rounds,
By mastering these 20 DSA patterns
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
Best DSA Resources: 👇
https://t.me/coderslearning
All the best 👍👍
By mastering these 20 DSA patterns
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
Best DSA Resources: 👇
https://t.me/coderslearning
All the best 👍👍