YouTube Summaries | Top 6 Coding Interview Concepts (Data Structures and Algorithms)

November 1st, 2023

##Summary of Top 6 Coding Interview Concepts

  1. Hashmaps: Hashmaps are fundamental data structures used for efficient data storage, retrieval, and manipulation. They are crucial for various problem-solving scenarios, such as finding pairs of elements that sum to a target value (e.g., the “Two Sum” problem).

  2. Recursion: Recursion is a powerful technique where a function calls itself to solve problems. It is widely used in coding interview questions, particularly in tree and graph-related problems.

  3. Depth First Search (DFS) and Breadth First Search (BFS): DFS and BFS are essential graph traversal algorithms that find applications in various problem-solving scenarios, from tree traversals to graph algorithms, including finding the shortest path.

  4. Binary Search: Binary search is an efficient searching algorithm that divides a sorted array or list into two parts, repeatedly narrowing down the search space by half. It’s a common technique used in searching and optimizing solutions for problems.

  5. Sliding Window: Sliding window is a technique for maintaining a “window” of elements in an array or list. It’s often used to solve problems that involve finding subarrays with specific properties, such as the maximum subarray sum.

  6. Heaps: Heaps are data structures used for tasks like quickly finding the minimum or maximum element. They are frequently employed in problems involving priority queues, such as finding the top k elements.

##Example Problems to Apply Concepts

  1. Hashmaps:

    • Two Sum: Given an array of integers, find two numbers that add up to a specific target number.
    • Longest Substring Without Repeating Characters: Find the length of the longest substring without repeating characters in a given string.
    • Frequency Counting: Count the frequency of elements in an array or string.

  2. Recursion:

    • Factorial: Write a recursive function to compute the factorial of a number.
    • Fibonacci Sequence: Generate the nth number in the Fibonacci sequence using recursion.
    • Towers of Hanoi: Solve the Towers of Hanoi puzzle recursively.

  3. Depth First Search (DFS) and Breadth First Search (BFS):

    • Graph Traversal: Traverse a graph to find connected components or paths between nodes.
    • Word Ladder: Transform one word into another by changing one letter at a time, using BFS to find the shortest transformation sequence.
    • Tree Traversals: Perform pre-order, in-order, and post-order traversals of a binary tree using DFS.

  4. Binary Search:

    • Search in a Sorted Array: Find the index of a target element in a sorted array using binary search.
    • Square Root Calculation: Calculate the square root of a number using binary search.
    • Search in a Rotated Sorted Array: Search for an element in a rotated sorted array using binary search.

  5. Sliding Window:

    • Maximum Subarray Sum: Find the maximum sum of a subarray of a fixed size k.
    • Longest Substring with K Distinct Characters: Find the longest substring with at most k distinct characters.
    • Minimum Window Substring: Find the minimum window in a string that contains all characters of another string.

  6. Heaps:

    • Kth Largest Element: Find the kth largest element in an array using a max heap.
    • Top K Frequent Elements: Find the k most frequent elements in an array using a min heap.
    • Merge K Sorted Lists: Merge k sorted linked lists into one sorted list using a min-heap for efficient merging.