Group Anagrams

Problem Number: 49 Difficulty: Medium Category: Array, Hash Table, String, Sorting LeetCode Link: https://leetcode.com/problems/group-anagrams/

Problem Description

Given an array of strings strs, group the anagrams together. You can return the answer in any order.

An Anagram is a word or phrase formed by rearranging the letters of a different word or phrase, typically using all the original letters exactly once.

Example 1:

Input: strs = ["eat","tea","tan","ate","nat","bat"]
Output: [["bat"],["nat","tan"],["ate","eat","tea"]]

Example 2:

Input: strs = [""]
Output: [[""]]

Example 3:

Input: strs = ["a"]
Output: [["a"]]

Constraints:

1 <= strs.length <= 10^4
0 <= strs[i].length <= 100
strs[i] consists of lowercase English letters

My Approach

I used a Hash Table approach with sorted string keys. The key insight is to use the sorted version of each string as a key to group anagrams together, since anagrams have the same characters when sorted.

Algorithm:

Handle edge case: if array has less than 2 elements, return the array as is
Create a hash map to store groups of anagrams
For each string, sort its characters to create a key
Use the sorted string as key and group original strings together
Return all groups from the hash map

Solution

The solution uses a hash table with sorted string keys to group anagrams. See the implementation in the solution file.

Key Points:

Uses hash table to group anagrams efficiently
Sorts characters of each string to create unique keys
Handles edge cases like empty array or single element
Groups strings with same sorted representation together
Returns all groups in any order

Time & Space Complexity

Time Complexity: O(n × k log k)

n is the number of strings
k is the maximum length of any string
Sorting each string takes O(k log k) time
Total: O(n × k log k)

Space Complexity: O(n × k)

Hash table stores all strings
Each string can be up to length k
Total: O(n × k)

Key Insights

Sorted String as Key: Anagrams have the same characters when sorted, making them perfect keys for grouping.
Hash Table Efficiency: Using a hash table provides O(1) average time for insertions and lookups.
Edge Case Handling: Arrays with less than 2 elements can be returned directly.
Character Sorting: Sorting characters creates a canonical representation for anagrams.
Grouping Strategy: All strings with the same sorted representation are anagrams of each other.
Flexible Output: The problem allows returning groups in any order.

Mistakes Made

Inefficient Key Generation: Initially might use character frequency counting instead of sorting.
Wrong Data Structure: Not using a hash table for efficient grouping.
Edge Case Missing: Not properly handling arrays with single elements or empty strings.
Complex Logic: Overcomplicating the grouping process.

Valid Anagram (Problem 242): Check if two strings are anagrams
Find All Anagrams in a String (Problem 438): Find all anagrams of a pattern in a string
Longest Common Prefix (Problem 14): Find common prefix among strings
Group Shifted Strings (Problem 249): Group strings that can be shifted to each other

Alternative Approaches

Character Frequency: Use character count arrays as keys - O(n × k) time
Prime Number Product: Use product of prime numbers for each character - O(n × k) time
Bit Manipulation: Use bit masks for character representation (limited to 26 characters)

Common Pitfalls

Wrong Key Generation: Not using sorted strings or character frequency as keys.
Inefficient Sorting: Sorting strings repeatedly instead of using efficient key generation.
Edge Cases: Not handling arrays with single elements or empty strings.
Memory Usage: Not considering the space complexity of storing all strings.
Output Format: Not returning the correct nested array structure.

Note: This is a classic hash table problem that demonstrates efficient grouping using sorted string keys.

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