As a developer preparing for coding interviews, you know how daunting it can be to tackle complex problems and algorithms. But what if you could master a set of essential coding patterns that would make all the difference? In this article, we’ll explore 15 fundamental coding interview patterns that will help you crack tech interviews with ease.
These patterns are not only commonly used in FAANG and Big Tech interviews but also cover a wide range of problems, from data structures and algorithms to system design and binary tree traversals. By mastering these patterns, you’ll be able to approach problems with confidence and solve them efficiently.
Let’s dive into the 15 essential coding interview patterns:
1. **Two Pointers**: This versatile pattern involves using two pointers to traverse arrays or linked lists efficiently. It’s widely used for problems like finding middle elements, detecting cycles, or reversing linked lists.
2. **Prefix Sum**: By precomputing cumulative sums, you can solve range-based problems efficiently. This pattern is essential for solving array-based problems like Subarray Sum Equals K.
3. **Sliding Window**: This powerful pattern optimizes problems involving contiguous subarrays. It’s a game-changer for problems like Longest Substring Without Repeating Characters or Maximum Sum of Subarray of Size K.
4. **Fast & Slow Pointers**: Also known as Floyd’s Cycle Detection, this pattern is commonly used for cycle detection in Linked Lists. It’s also useful for detecting meeting points in sequences.
5. **LinkedList In-Place Reversal**: This pattern focuses on reversing linked lists without extra space. It’s an essential technique when working with memory constraints.
6. **Monotonic Stack**: The Monotonic Stack is a structured stack that maintains elements in sorted order (increasing or decreasing). It’s useful for solving problems involving the next greater or smaller element.
7. **Top ‘K’ Elements**: This pattern efficiently finds top K largest, smallest, or most frequent elements. You can use this pattern to solve problems like finding the Kth largest element in a given array.
8. **Overlapping Intervals**: This pattern deals with problems involving intervals (e.g., time ranges, numeric ranges) where you need to detect, merge, or manipulate overlapping segments.
9. **Modified Binary Search**: Modified Binary Search optimizes searching in sorted or rotated arrays. It’s essential for solving problems like Binary Search or Search in Rotated Sorted Array.
10. **Binary Tree Traversal**: This pattern involves traversing binary trees using various techniques like inorder, pre-order, and post-order traversal. It’s also useful for solving tree-related problems.
11. **Depth-First Search (DFS)**: DFS explores nodes level by level, often implemented with a queue. It’s widely used for solving binary tree-related patterns and graph traversal problems.
12. **Breadth-First Search (BFS)**: BFS explores nodes level by level, often implemented with a queue. It’s useful for solving binary tree-related patterns and graph traversal problems.
13. **Matrix Traversal**: Matrix Traversal involves navigating 2D arrays to solve problems like searching, counting paths, or collecting elements.
14. **Backtracking**: Backtracking is a recursive algorithmic pattern for solving problems by exploring all possible solutions incrementally. It’s useful for solving combinatorial problems with constraints.
15. **Dynamic Programming Patterns**: Dynamic Programming focuses on breaking problems into subproblems and solving them optimally. You can develop patterns by solving problems like the knapsack problem.
By mastering these 15 essential coding interview patterns, you’ll be well-prepared to tackle a wide range of problems and algorithms in your coding interviews. Remember to practice consistently with platforms like LeetCode, Educative-99, or Grokking Coding Interview Patterns for Interviews to improve your skills.
Source: https://dev.to/somadevtoo/coding-interviews-was-hard-until-i-learned-these-patterns-2ji7