Let’s dive into the frequently asked coding interview topic now: Hashing & Maps

Hashing helps us access data quickly, making it a critical topic in coding interviews. HashMaps (or dictionaries) provide constant-time access and are used to solve problems like counting elements, finding duplicates, and mapping data efficiently.

3.1. Use Hash Maps for Fast Lookups

Example:
Check if two strings are anagrams.
Given s1 = "listen", s2 = "silent", are they anagrams?

Solution:
Use a hash map to count the frequency of characters in both strings and compare the counts.

Concept tested:
Efficient searching and counting with O(1) average time complexity.


3.2. Count Frequency of Elements

Example:
Given an array nums = [1, 2, 2, 3, 3, 3, 4], count the frequency of each element.

Solution:
Use a hash map to store the counts:
{1: 1, 2: 2, 3: 3, 4: 1}

It tests how well you can group data efficiently and manage it using hash-based structures.


3.3. Find Duplicates

Example:
Given arr = [4, 5, 6, 7, 5, 8], find the first duplicate.

Solution:
Use a hash map to track seen elements as you traverse the array. If you encounter an element already in the map, it’s a duplicate.

It tests your ability to solve problems with constant time lookups for duplicates.


3.4. Two Sum Problem

Example:
Given nums = [2, 7, 11, 15] and target = 9, return indices of the two numbers that add up to the target.

Solution:
Use a hash map to track the difference between the target and the current number. When you find a match, return the indices.

Concept tested:
Efficient search for pairs in a single pass with O(n) time complexity.


3.5. Implement LRU Cache

Example:
Design a cache that stores the most recently used items, evicting the least recently used when it exceeds its capacity.

Solution:
Use a hash map to store the cache and a doubly linked list to keep track of the order of usage. Combine both to make retrieval and eviction O(1).

This tests your ability to combine hash maps with other data structures like linked lists, and to implement efficient solutions with constraints.


Hash maps are frequently used in problems involving counting, grouping, and mapping, especially when you need to reduce time complexity from quadratic to linear.


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Top 7 Coding Interview Concepts: https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X/720

Top 7 Python Concepts: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L/1452

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