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

IntermediatePrefer not to say
Jun 2026

Summary

Got a Meta SWE coding round with a bitmask/subset problem that looked deceptively clean on the surface. The constraint about duplicate letters within a word being auto-invalid is the kind of thing that trips you up if you're not careful.

Questions Asked (1)

Q1

Given a list of words, choose a subset where no two words share any letter, and maximize the total number of unique characters covered. Words with repeated letters internally are invalid. Return the maximum unique character count.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

The auto-disqualification of words with internal duplicate letters (like 'apple') is easy to miss if you jump straight to the subset logic.

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AI HintsAI Generated

Suggested Approach

First, validate and preprocess each word by checking for duplicate letters and converting it to a bitmask. Then, use backtracking to explore all valid subsets, pruning branches when the current union of characters cannot exceed the best found so far. Return the maximum bit count among valid subsets.

Pro tip: Mention that you can deduplicate words by their bitmask and sort them by popcount descending to improve pruning. Also, note that the maximum possible answer is 26, so you can early-exit if you reach that.

1. Validate and Convert Words

Iterate through the list, discard any word with repeated letters, and represent each valid word as a 26-bit integer mask.

2. Deduplicate and Sort

Remove duplicate masks and sort the remaining masks in descending order of their popcount to prioritize words that cover more unique characters.

3. Backtracking with Pruning

Recursively explore subsets, maintaining the current union mask. At each step, if the union already has no overlap with the next word's mask, include it; otherwise skip. Prune if the current union's popcount plus the sum of remaining words' popcounts cannot exceed the best found.

4. Track and Return Maximum

Keep a global maximum of the popcount of the union mask. After exploring all valid subsets, return this maximum.

Key Points to Mention

  • Bitmask representation for efficient set operations (AND, OR, popcount).
  • Preprocessing to filter out invalid words with duplicate letters.
  • Backtracking with pruning to avoid exploring all 2^n subsets.
  • Deduplication of words with identical character sets.
  • Sorting words by popcount descending to improve pruning effectiveness.
  • Early termination when the maximum possible unique characters (26) is reached.

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