I Solved One Coding Interview Question 4 Different Ways

Watch a mock coding interview where one classic algorithm question gets solved four completely different ways, each optimizing for a different constraint. This coding interview starts with the Group Anagrams problem and escalates through increasingly difficult variations that test how deep a candidate can really go. The interview begins with the standard approach — sorting strings to use as hash map keys for grouping anagrams. From there, the interviewer introduces new constraints one at a time: handling duplicate strings, optimizing for extremely long strings where sorting becomes too expensive, and finally dealing with millions of possible Unicode characters where even a fixed-size array won't fit in memory. Each variation forces a fundamentally different solution strategy, from hash maps to character counting with Python's Counter to space-efficient representations. 0:00 Introduction and problem setup 0:45 Reading the Group Anagrams problem 1:20 Clarifying what defines an anagram 2:00 First approach: sorted string as hash key 4:30 Analyzing time complexity (N * A log A) 5:15 Coding the sorted key solution in Python 8:00 Testing and verifying output 9:30 Discussing hash map vs array trade-offs 12:00 Variation 2: handling duplicate strings 14:30 Adding visited set to filter duplicates 16:00 Variation 3: extremely long strings, small input 18:00 Why sorting becomes too expensive 19:15 Character counting approach with Python Counter 22:00 Coding the counter-based solution 24:00 Variation 4: millions of Unicode characters 25:30 Memory constraints with large character sets 26:15 Discussion of alternative representations and hashing 27:00 Wrap-up, feedback, and career discussion Problem covered: Group Anagrams (LeetCode 49): https://leetcode.com/problems/group-anagrams/