Sorted each string as a key and used a hashmap to bucket words together.
Clarify the problem constraints (e.g., input size, character set) and then propose a hash map approach where the key is a canonical representation of each anagram group (e.g., sorted string or character count). Iterate through the array, group strings by key, and return the grouped values. Discuss time/space complexity and potential optimizations.
Pro tip: Mention that sorting each string as a key takes O(N * K log K) time, but using a character count key can reduce it to O(N * K) for a fixed alphabet, showing awareness of optimization. Also, note that Apple values clean, efficient code and often asks about edge cases like empty strings or Unicode characters.
Ask about input size, character set (lowercase English letters? Unicode?), and whether the output order matters. This shows attention to detail and helps choose the right approach.
Decide on a representation that uniquely identifies anagrams: sorted string or character frequency count. Explain trade-offs (sorting vs counting) in terms of time and space.
Use a hash map to group strings by their canonical key. Iterate through the input array, compute the key for each string, and append the string to the corresponding list.
State the time and space complexity. For sorting approach: O(N * K log K) time, O(N * K) space. For counting approach: O(N * K) time, O(N * K) space.
Mention handling of empty strings, strings with different lengths, and potential memory optimizations. Optionally, discuss alternative approaches like using a prime number product key (with caution for overflow).
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