Is Valid Anagram easy or hard?

Valid Anagram is classified as an Easy problem on LeetCode with a high acceptance rate. The challenge focuses on recognizing that character frequency comparison is more efficient than sorting.

Valid Anagram Python/Java solution

In Python, the common approach uses a dictionary or a 26-length list to track character frequencies. In Java, developers typically use an int array of size 26 or a HashMap . Both implementations achieve O(n) time complexity with constant extra space for lowercase letters.

How to solve Valid Anagram in O(n)?

Use a frequency array or hash map to count characters. First iterate through string s and increment the count for each character. Then iterate through t and decrement the corresponding counts. If any count becomes negative or the lengths differ, the strings are not anagrams. Processing each character once gives O(n) time complexity.

What is the best approach for Valid Anagram?

The frequency counting approach is the most efficient. Count the occurrence of each character in the first string and subtract counts while scanning the second string. If all counts return to zero, the strings are anagrams. This runs in O(n) time with O(1) space for a fixed alphabet.

Is Valid Anagram asked at Google/Amazon/Meta?

Valid Anagram appears frequently in technical interview practice sets and has been reported in screening rounds for companies such as Amazon, Meta, and Google. The problem tests understanding of hash tables, string processing, and time complexity optimization.

What data structure is used in Valid Anagram?

The optimal solution uses a hash table or a fixed-size frequency array. The structure stores how many times each character appears. Updating counts while scanning the strings allows constant-time lookups and efficient verification.

What is the time complexity of Valid Anagram?

The optimal solution runs in O(n) time because each character in the strings is processed once. The sorting approach takes O(n log n) due to the sorting step. Frequency counting with a hash table or fixed-size array achieves linear time.