Knew the sorted-key trick going in but still spent like two minutes overthinking whether a hash of character counts would be faster.
Use a hash map to group strings by a canonical key that represents their character frequencies. For each string, compute the key (e.g., sorted string or frequency tuple) and append the string to the corresponding group. Finally, return all groups as a list of lists.
Pro tip: Discuss trade-offs between sorting each string (O(n * k log k)) and using a frequency count key (O(n * k)), and mention that the frequency approach is more efficient for large alphabets or long strings. Also, clarify that the order of groups and strings within groups doesn't matter unless specified.
Ask about input size, character set (e.g., lowercase letters only?), and whether the output order matters. This shows attention to detail and helps choose the optimal approach.
Decide on a key that uniquely identifies anagrams: either the sorted string or a frequency count (e.g., a tuple of 26 counts for lowercase letters). Explain why the key works.
Initialize a hash map. For each string, compute its key and append the string to the list associated with that key in the map.
Extract all values from the hash map and return them as a list of lists. Mention that the order of groups is arbitrary.
State the time and space complexity: O(n * k) for frequency key (where n is number of strings, k is max length) or O(n * k log k) for sorting, and O(n * k) space for storing the groups.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.