This repository contains C++ implementations of various data structures and algorithms. The code is organized into directories based on the data structure or algorithm being implemented.
The following patterns can be used to solve many problems related to data structures and algorithms in technical interviews.
- Sliding Window
- Islands (Matrix Traversal)
- Two Pointers
- Fast & Slow Pointers
- Merge Intervals
- Cyclic Sort
- In-place Reversal of a LinkedList
- Tree Breadth-First Search
- Tree Depth First Search
- Two Heaps
- Subsets
- Modified Binary Search
- Bitwise XOR
- Top ‘K’ Elements
- K-way Merge
- Topological Sort
- 0/1 Knapsack
- Fibonacci Numbers
- Palindromic Subsequence
- Longest Common Substring
Here are some tips that can help you solve coding questions efficiently:
- If the input array is sorted, consider using Binary Search, Two Pointers, or Binary Search for finding for certain range and want less than that range.
- If you want to find the next element, consider using a stack.
- If the input is a binary tree, consider using DFS (Preorder, Inorder, Postorder) or BFS (Level Order).
- If the input is a binary search tree, consider using Left < Cur < Right and Inorder Traversal.
- If the input is a matrix/graph, consider using DFS (Recursion, Stack) or BFS (Queue).
- To find the shortest/nearest path/distance in a tree/matrix/graph, consider using BFS (non-weighted) or Dijkstra (weighted).
- For string concatenation, consider using StringBuilder or String.join().
- If the input is a linked list, consider using a Dummy Node, Two Pointers, or Fast & Slow Pointers.
- If you need to compute the same input multiple times, consider using Memoization (DP).
- If recursion is banned, consider using a Stack.
- To compute permutations/combinations/subsets, consider using Backtracking.
- To find the top/least Kth element, consider using QuickSelect or Heap.
- For common strings, consider using Map or Trie.
- For sorting, consider using Quick Sort, Merge Sort, or built-in sorts.
- To find the smallest/largest/median in a stream, consider using Two Heaps.
- For maximum/minimum subarray/subset/options, consider using Dynamic Programming.
- For Map/Set, the time complexity is O(1) and space complexity is O(n).
- For Deque, you can replace Stack, Queue, and LinkedList.
This project is licensed under the MIT License. Feel free to use the code for your personal or commercial projects. However, I cannot be held responsible for any issues or problems that arise from the use of this code.