Goldman Sachs·Software Engineer·Onsite - Coding / Algorithms·Intermediate

Intermediate

Apr 2026

Summary

Goldman Sachs software engineer interview with a coding round that leaned heavily on string manipulation and algorithmic trade-offs. The anagram grouping problem sounds straightforward but they pushed pretty hard on the complexity analysis side of things.

Questions Asked (1)

Given an array of strings, group all anagrams together and return them as a list of groups. Then walk through two different approaches: one using a sorted string as a hash map key, and one using a character count as the key. Analyze the time and space complexity of each.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

I went straight for the sorted-key approach because it's the one I'd practiced most.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by clarifying the problem and edge cases, then present the sorted-string key approach as a baseline, followed by the character-count key approach as an optimization. For each, explain the algorithm, walk through a small example, and analyze time and space complexity, highlighting trade-offs.

Pro tip: Emphasize that the character-count key avoids sorting and can be more efficient for long strings, but requires careful encoding to avoid collisions; mention that in practice, the sorted-string approach is often simpler and fast enough due to short strings.

1. Clarify requirements and edge cases

Ask about input constraints (string length, character set, number of strings) and expected output format. Discuss edge cases like empty strings, single-character strings, and duplicate groups.

2. Present sorted-string key approach

Explain that sorting each string yields a canonical key; use a hash map to group strings with the same key. Provide a code sketch or pseudocode.

3. Analyze sorted-string approach complexity

Time: O(N * K log K) where N is number of strings and K is max length; space: O(N * K) for the hash map and output. Mention that sorting dominates.

4. Present character-count key approach

Explain that counting character frequencies yields a key (e.g., a tuple of counts or a delimited string). Use a hash map to group anagrams. Provide pseudocode.

5. Analyze character-count approach complexity and compare

Time: O(N * K) since counting is linear; space: O(N * K) for keys and output. Compare with sorted approach: better asymptotic time for large K, but keys may be larger; discuss trade-offs.

Key Points to Mention

Hash map usage for grouping
Canonical key generation (sorted string vs. character count)
Time complexity: O(N * K log K) vs. O(N * K)
Space complexity: O(N * K) for both, but keys differ in size
Trade-offs: simplicity vs. efficiency, especially for long strings
Handling edge cases: empty strings, Unicode, large inputs

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