Bloomberg·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

Apr 2026

Summary

Bloomberg coding round, one problem the whole session. The question looked clean on the surface but the follow-up constraints are where it got interesting.

Questions Asked (1)

Given an array of strings, group them into anagram clusters and return all the groups in any order. Aim for near-linear time in total characters, avoid sorting each string if possible, and explain how you'd handle case sensitivity, non-ASCII input, and very long strings.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

My first instinct was to sort each string and use that as a map key, which is the obvious O(n * k log k) approach.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and edge cases, then propose a hash map keyed by a canonical representation of each string's character counts. Use a fixed-size array or a custom encoding to avoid sorting, achieving O(total characters) time. Discuss trade-offs for case sensitivity, non-ASCII, and long strings, and mention memory considerations.

Pro tip: Mention that for Unicode, you can use a hash of the sorted code points or a frequency map of code points, but be aware of normalization (e.g., NFC vs NFD) and consider using a library if needed. Also, for very long strings, streaming the character counts can reduce memory.

1. Clarify requirements and edge cases

Ask about case sensitivity (e.g., 'Listen' vs 'Silent'), non-ASCII characters (Unicode), and constraints on string length and total input size. Confirm if groups can be returned in any order and if the input array can be modified.

2. Design canonical key without sorting

For ASCII, use a 26-element count array and convert to a string or tuple as the key. For Unicode, use a hash map of code point frequencies or a sorted list of code points if sorting is acceptable; alternatively, use a polynomial hash of counts.

3. Implement grouping with hash map

Iterate through each string, compute its key, and append the string to the corresponding list in a hash map. Finally, return the map's values as the list of groups.

4. Analyze complexity and trade-offs

Explain that time is O(total characters) for counting plus O(number of strings) for hashing, assuming constant-time key operations. Space is O(total characters) for the output plus O(number of unique keys) for the map. Discuss that sorting each string would be O(n log n) per string, which is worse.

5. Address edge cases and extensions

Handle empty strings, strings with different cases by normalizing (e.g., to lowercase), and non-ASCII by using code point counts. For very long strings, consider streaming counts or using a rolling hash to avoid storing the entire string.

Key Points to Mention

Use character frequency counting as the key instead of sorting to achieve near-linear time.
For ASCII, a fixed-size array of 26 integers can be encoded as a string or tuple for the hash key.
For Unicode, use a hash map of code point frequencies or a sorted list of code points, and be aware of normalization forms.
Case sensitivity can be handled by normalizing all strings to a consistent case (e.g., lowercase) before processing.
Very long strings: consider streaming the character counts to avoid storing the entire string, or use a rolling hash if memory is a concern.
Time complexity: O(total characters) for counting, plus O(number of strings) for hash map operations; space complexity: O(total characters) for output and O(unique keys) for the map.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.