Introduction
Are you preparing for MAANG (Microsoft, Amazon, Apple, Netflix, Google) or FAANG (Facebook, Amazon, Apple, Netflix, Google) interviews? Are you looking to crack FAANG in 3 months? How can one prepare for FAANG in 6 months, and what are effective strategies to enhance problem-solving skills? While solving hundreds of coding questions is one approach, there are coding patterns that can provide you with a structured and efficient way to tackle coding problems. In this article, We will explore 20 coding patterns that can assist you in interviews and significantly boost your chances of success.
1. Sliding Window
Data Structure Involved: Array, String, HashTable
Usage: This algorithmic technique is used when we need to handle the input data in a specific window size. It is particularly useful for solving problems such as finding the longest substring with 'K' distinct characters or dividing fruits into baskets.
Sample Problems:
Usage: This algorithmic technique is used when we need to handle the input data in a specific window size. It is particularly useful for solving problems such as finding the longest substring with 'K' distinct characters or dividing fruits into baskets.
Sample Problems:
2. Islands (Matrix Traversal)
Data Structure Involved: Matrix, Queue
Usage: This pattern describes all the efficient ways of traversing a matrix (or 2D array). It is commonly used for solving problems related to counting the number of islands, flood fill, and detecting cycles in a matrix.
Sample Problems:
Usage: This pattern describes all the efficient ways of traversing a matrix (or 2D array). It is commonly used for solving problems related to counting the number of islands, flood fill, and detecting cycles in a matrix.
Sample Problems:
3. Two Pointers
Data Structure Involved: Array, String, LinkedList
Usage: This technique uses two pointers to iterate through the input data. Generally, both pointers move in the opposite direction at a constant interval. It is useful for solving problems like squaring a sorted array, the Dutch National Flag problem, and finding the minimum window sort.
Sample Problems:
Usage: This technique uses two pointers to iterate through the input data. Generally, both pointers move in the opposite direction at a constant interval. It is useful for solving problems like squaring a sorted array, the Dutch National Flag problem, and finding the minimum window sort.
Sample Problems:
4. Fast and Slow Pointers
Data Structure Involved: Array, String, LinkedList
Usage: Also known as the Hare and Tortoise algorithm, this technique uses two pointers that traverse the input data at different speeds. It is commonly used for detecting cycles in linked lists, finding the middle of a linked list, and identifying cycles in a circular array.
Sample Problems:
Usage: Also known as the Hare and Tortoise algorithm, this technique uses two pointers that traverse the input data at different speeds. It is commonly used for detecting cycles in linked lists, finding the middle of a linked list, and identifying cycles in a circular array.
Sample Problems:
5. Merge Intervals
Data Structure Involved: Array, Heap
Usage: This technique is used to deal with overlapping intervals. It is helpful for solving problems like conflicting appointments and finding the minimum number of meeting rooms required.
Sample Problems:
Usage: This technique is used to deal with overlapping intervals. It is helpful for solving problems like conflicting appointments and finding the minimum number of meeting rooms required.
Sample Problems:
6. Cyclic Sort
Data Structure Involved: Array
Usage: Use this technique to solve array problems where the input data lies within a fixed range. It helps in finding all missing numbers, all duplicate numbers, and the first K missing positive numbers.
Sample Problems:
Usage: Use this technique to solve array problems where the input data lies within a fixed range. It helps in finding all missing numbers, all duplicate numbers, and the first K missing positive numbers.
Sample Problems:
7. In-place Reversal of a LinkedList
Data Structure Involved: LinkedList
Usage: This technique describes an efficient way to reverse the links between a set of nodes of a LinkedList. Often, the constraint is to perform this reversal in-place, using the existing node objects and without using extra memory.
Sample Problems:
Usage: This technique describes an efficient way to reverse the links between a set of nodes of a LinkedList. Often, the constraint is to perform this reversal in-place, using the existing node objects and without using extra memory.
Sample Problems:
8. Breadth-First Search
Data Structure Involved: Tree, Graph, Matrix, Queue
Usage: This technique is used to solve problems involving traversing trees or graphs in a breadth-first search manner. It is useful for problems like binary tree level order traversal and finding the minimum depth of a binary tree.
Sample Problems:
Usage: This technique is used to solve problems involving traversing trees or graphs in a breadth-first search manner. It is useful for problems like binary tree level order traversal and finding the minimum depth of a binary tree.
Sample Problems:
9. Depth First Search
Data Structure Involved: Tree, Graph, Matrix
Usage: This technique is used to solve problems involving traversing trees or graphs in a depth-first search manner. It is often used for problems like finding a path with a given sequence and counting paths for a sum.
Sample Problems:
Usage: This technique is used to solve problems involving traversing trees or graphs in a depth-first search manner. It is often used for problems like finding a path with a given sequence and counting paths for a sum.
Sample Problems:
10. Two Heaps
Data Structure Involved: Heap, Array
Usage: In many problems, we are given a set of elements that can be divided into two parts. This technique helps in finding the smallest element in one part and the largest element in the other part. It utilizes a Min-Heap to find the smallest element and a Max-Heap to find the largest element.
Sample Problems:
Usage: In many problems, we are given a set of elements that can be divided into two parts. This technique helps in finding the smallest element in one part and the largest element in the other part. It utilizes a Min-Heap to find the smallest element and a Max-Heap to find the largest element.
Sample Problems:
11. Subsets
Data Structure Involved: Queue, Array, String
Usage: Use this technique to generate subsets or solve problems that involve permutations or combinations of a set of elements.
Sample Problems:
Usage: Use this technique to generate subsets or solve problems that involve permutations or combinations of a set of elements.
Sample Problems:
12. Modified Binary Search
Data Structure Involved: Array
Usage: This technique is used to efficiently search a sorted set of elements. It is helpful for problems like finding the ceiling of a number and determining the maximum element in a bitonic array.
Sample Problems:
Usage: This technique is used to efficiently search a sorted set of elements. It is helpful for problems like finding the ceiling of a number and determining the maximum element in a bitonic array.
Sample Problems:
13. Bitwise XOR
Data Structure Involved: Array, Bits
Usage: This technique uses the XOR operator to manipulate bits and solve problems efficiently. It is useful for solving problems like finding two single numbers in an array and flipping and inverting an image.
Sample Problems:
Usage: This technique uses the XOR operator to manipulate bits and solve problems efficiently. It is useful for solving problems like finding two single numbers in an array and flipping and inverting an image.
Sample Problems:
14. Top 'K' Elements
Data Structure Involved: Array, Heap, Queue
Usage: This technique is used to find the top/smallest/frequently occurring 'K' elements in a set. It involves using data structures like an array, heap, or queue.
Sample Problems:
Usage: This technique is used to find the top/smallest/frequently occurring 'K' elements in a set. It involves using data structures like an array, heap, or queue.
Sample Problems:
15. K-way Merge
Data Structure Involved: Array, Queue, Heap
Usage: This technique helps in solving problems that involve a list of sorted arrays. It is used to merge 'K' sorted arrays efficiently.
Sample Problems:
Usage: This technique helps in solving problems that involve a list of sorted arrays. It is used to merge 'K' sorted arrays efficiently.
Sample Problems:
16. Topological Sort
Data Structure Involved: Array, HashTable, Queue, Graph
Usage: Use this technique to find a linear ordering of elements that have dependencies on each other. It is commonly used for solving problems like task scheduling and determining the order of characters in an alien dictionary.
Sample Problems:
Usage: Use this technique to find a linear ordering of elements that have dependencies on each other. It is commonly used for solving problems like task scheduling and determining the order of characters in an alien dictionary.
Sample Problems:
17. 0/1 Knapsack
Data Structure Involved: Array, HashTable
Usage: This technique is used to solve optimization problems where we need to select elements from a given set with a limitation on capacity, and each element can only be picked once. It is useful for problems like equal subset sum partition and finding the minimum subset sum difference.
Sample Problems:
Usage: This technique is used to solve optimization problems where we need to select elements from a given set with a limitation on capacity, and each element can only be picked once. It is useful for problems like equal subset sum partition and finding the minimum subset sum difference.
Sample Problems:
18. Fibonacci Numbers
Data Structure Involved: Array, HashTable
Usage: Utilize this powerful technique to solve problems based on the Fibonacci numbers sequence, where each subsequent number is derived from the last few numbers. Enhance your problem-solving skills with this unique approach.
Sample Problems:
Usage: Utilize this powerful technique to solve problems based on the Fibonacci numbers sequence, where each subsequent number is derived from the last few numbers. Enhance your problem-solving skills with this unique approach.
Sample Problems:
19. Top 'K' Frequencies
Data Structure Involved: Array, HashTable, Heap
Usage: This technique is used to find the top 'K' frequent elements in a set. It involves using data structures like a hash table and a heap.
Sample Problems:
Usage: This technique is used to find the top 'K' frequent elements in a set. It involves using data structures like a hash table and a heap.
Sample Problems:
20. Topological Sort (Graph)
Data Structure Involved: Graph, Array, Queue
Usage: This technique is used to find a linear ordering of elements in a directed acyclic graph (DAG). It helps in solving problems like course scheduling and determining the order of tasks based on their prerequisites.
Sample Problems:
Usage: This technique is used to find a linear ordering of elements in a directed acyclic graph (DAG). It helps in solving problems like course scheduling and determining the order of tasks based on their prerequisites.
Sample Problems:
Conclusion
In this article, we have explored 20 coding patterns that can help you master MAANG interviews. Instead of solely focusing on solving hundreds of coding questions, these coding patterns provide a structured approach to problem-solving. By understanding and practicing these patterns, you can enhance your problem-solving skills and improve your performance in coding interviews.
Remember, it's important to gain hands-on experience by implementing these patterns in your coding projects and practicing them through coding challenges. As you become familiar with these patterns, you'll develop a deeper understanding of their applications and be better equipped to tackle complex coding problems.
To further enhance your coding skills, we recommend referring to the books "Grokking the Coding Interview" and "Grokking Dynamic Programming" by DesignGurus.org. These resources provide in-depth explanations, examples, and practice problems to help you strengthen your knowledge of these coding patterns.
Keep learning, practicing, and pushing your boundaries to stand out from the competition. Happy coding!
Remember, it's important to gain hands-on experience by implementing these patterns in your coding projects and practicing them through coding challenges. As you become familiar with these patterns, you'll develop a deeper understanding of their applications and be better equipped to tackle complex coding problems.
To further enhance your coding skills, we recommend referring to the books "Grokking the Coding Interview" and "Grokking Dynamic Programming" by DesignGurus.org. These resources provide in-depth explanations, examples, and practice problems to help you strengthen your knowledge of these coding patterns.
Keep learning, practicing, and pushing your boundaries to stand out from the competition. Happy coding!
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