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Google·Software Engineer·Onsite - Coding / Algorithms·Intermediate

IntermediatePrefer not to say
Apr 2026

Summary

Google SWE coding round with a pretty gnarly string/subsequence problem that took me a while to even parse correctly. The problem statement alone felt like a puzzle before I even touched the algorithm.

Questions Asked (1)

Q1

Given a string s, determine whether every subsequence of s with length 3 or more can be rearranged into a valid English dictionary word. Return true if this holds for all such subsequences, false otherwise.

Algorithms & Data StructuresAdaptability & Ambiguity
Author's notes

I spent way too long just re-reading the problem.

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AI HintsAI Generated

Suggested Approach

First, clarify the problem's constraints and assumptions, especially the definition of 'valid English dictionary word' and the size of the dictionary. Then, reason about the combinatorial explosion: if the string length is n, there are O(n^3) subsequences of length 3, and checking each against a dictionary is expensive. Instead, derive necessary conditions: for the property to hold, every length-3 subsequence must be rearrangeable into a word, which implies the string's character multiset must be highly constrained. Finally, propose an efficient algorithm that checks these conditions without enumerating all subsequences.

Pro tip: Demonstrate adaptability by acknowledging the ambiguity in 'valid English dictionary word' and proposing a reasonable formalization (e.g., a fixed set of words) before diving into the algorithm. This shows you can handle underspecified problems, a key trait at Google.

1. Clarify the problem

Ask clarifying questions: What is the dictionary? Is it fixed? What is the maximum length of s? Can subsequences be rearranged into any word, or must the rearrangement be a permutation of the subsequence? Confirm that 'rearranged' means the characters can be reordered arbitrarily.

2. Analyze constraints and edge cases

Consider small strings (length < 3) where the condition is vacuously true. For longer strings, note that if any length-3 subsequence cannot be rearranged into a word, the answer is false. Thus, the property must hold for all length-3 subsequences, which is the most restrictive case.

3. Derive necessary conditions

For every triple of characters (with repetition allowed) that appears as a subsequence, their sorted multiset must match the sorted multiset of some dictionary word of length 3. This implies the set of characters in s must be a subset of characters that appear in length-3 words, and their frequencies must be limited.

4. Design an efficient algorithm

Preprocess the dictionary to extract all length-3 words and store their sorted character multisets in a hash set. Then, for the given string, check all O(n^3) subsequences? That's too slow. Instead, observe that if the string contains any character not in any length-3 word, return false. Also, if the string contains three characters that cannot form a word, return false. But checking all triples is still O(n^3). We can optimize by noting that the condition must hold for all triples, so we can check the set of distinct characters and their frequencies. If the string has more than 3 distinct characters, then any triple of three distinct characters must be a valid word; if not, return false. Similarly, for repeated characters, check pairs and triples. The key is to reduce the problem to checking a small set of character combinations.

5. Validate with examples and complexity

Test with examples: s = 'abc' where 'abc' is not a word, then false. s = 'a' then true. Discuss time complexity: O(n + D) where D is dictionary size, after preprocessing. Space complexity: O(D) for storing length-3 word multisets.

Key Points to Mention

  • Clarify the definition of 'valid English dictionary word' and the dictionary size.
  • Recognize that the condition must hold for all length-3 subsequences, making it the critical case.
  • Use preprocessing of the dictionary to create a set of valid length-3 character multisets.
  • Optimize by checking only distinct character combinations rather than all O(n^3) subsequences.
  • Consider edge cases: strings of length < 3, strings with characters not in any word, and strings with repeated characters.
  • Discuss time and space complexity, aiming for O(n + D) time after preprocessing.

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