Google·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Jun 2026

Summary

Google SWE coding round with a string problem that looks deceptively simple until you start thinking about how many substrings you actually have to check. The core challenge is anagram validation across all contiguous substrings of length 3 or more, and the dictionary lookup angle makes it more interesting than a typical sliding window question.

Questions Asked (1)

Given a string of letters and access to an English dictionary (as a set), return true if every contiguous substring of length 3 or more can be rearranged into a valid dictionary word. In other words, for every such substring, there must exist some word in the dictionary that is an anagram of it.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

The anagram-check part is fine, sort the characters or use a frequency map, compare against dictionary entries.

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AI HintsAI Generated

Suggested Approach

Clarify the problem constraints and edge cases, then propose an efficient solution using a canonical representation (e.g., sorted characters) for dictionary words and substrings. Discuss trade-offs between precomputing an anagram set and checking on the fly, and analyze time/space complexity.

Pro tip: Demonstrate awareness of the potential O(n^3) naive approach and optimize by precomputing a set of sorted dictionary words, then sliding a window of length 3 to check each substring in O(1) average time. Also, mention that you can early-exit if any substring fails.

1. Clarify requirements and constraints

Ask about input size, dictionary size, character set, and whether substrings of length >3 need to be checked or if length 3 suffices. Confirm that 'rearranged' means anagram.

2. Design a canonical representation

Choose a way to represent words and substrings such that anagrams map to the same key, e.g., sorted characters or character count signature.

3. Preprocess the dictionary

Convert each dictionary word to its canonical form and store in a hash set for O(1) lookups.

4. Check all substrings of length 3

Iterate over the string, extract each length-3 substring, compute its canonical form, and check if it exists in the set. If any fails, return false.

5. Analyze complexity and discuss trade-offs

Explain that checking only length-3 substrings is sufficient because any longer substring contains a length-3 substring that must also be an anagram of a dictionary word. Discuss time O(n) and space O(D) where D is dictionary size.

Key Points to Mention

Anagram equivalence via sorting or character counts
Hash set for O(1) average lookup
Sliding window for contiguous substrings
Sufficiency of checking length-3 substrings
Time and space complexity analysis
Edge cases: empty string, string length < 3, dictionary empty

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