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Meta·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Apr 2026

Summary

Meta SWE coding round with a string manipulation problem that looks like a word break variant but has a suffix-specific twist. Not a lot of context shared about how it went, just the problem itself.

Questions Asked (1)

Q1

Given a list of words and a list of target strings, determine for each target whether it can be formed by concatenating one or more words from the list (words can be reused). Return a boolean list.

Algorithms & Data Structures
Author's notes

Classic word break problem dressed up with a 'suffix' label, which threw me for a second because I kept thinking it meant something about actual string suffixes.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem constraints (e.g., word list size, target length, character set) and discuss the brute-force approach. Then, propose an efficient solution using dynamic programming (DP) where dp[i] indicates if the prefix of length i can be segmented. Optimize by iterating over words and checking if they match the substring ending at i, or by using a trie for faster lookups.

Pro tip: Mention that you can preprocess the word list to find the maximum word length and only check substrings up to that length, significantly reducing time complexity. Also, consider using a set for O(1) word lookups.

1. Clarify constraints and edge cases

Ask about input sizes, character set, and whether empty strings or empty word lists are possible. This shows attention to detail and helps choose the right algorithm.

2. Discuss brute-force and inefficiencies

Explain that a naive recursive approach would try all possible segmentations, leading to exponential time. This sets the stage for a more optimal solution.

3. Propose dynamic programming solution

Define dp[i] as whether the prefix of length i can be segmented. Initialize dp[0] = true. For each i from 1 to n, check all words: if dp[i - len(word)] is true and the substring matches, set dp[i] = true.

4. Optimize with trie or max word length

To avoid checking all words for each position, build a trie of the word list and traverse it from each i where dp[i] is true, or limit substring checks to the maximum word length.

5. Analyze complexity and test

State time complexity: O(n * m * L) for DP with word list, where n is target length, m is number of words, L is average word length; with trie, O(n * L). Space complexity O(n). Walk through an example to verify.

Key Points to Mention

  • Dynamic programming with boolean array for prefix segmentation
  • Using a set for O(1) word lookups
  • Optimization by limiting substring length to max word length
  • Trie data structure for efficient prefix matching
  • Handling multiple target strings by reusing the same DP logic per target
  • Time and space complexity analysis

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