← Meta Interview Insights

Meta·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
May 2026Remote

Summary

Meta SWE coding round, one problem the whole session. The problem itself was clean but I spent way too long second-guessing my approach before I even wrote a line of code.

Questions Asked (1)

Q1

Given an array of lowercase strings, find the maximum length of a concatenation of a subset of those strings such that every character in the result is unique across the whole concatenation.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

My first instinct was brute force all subsets, which is fine given the constraint of at most 16 words, but I wasted time trying to be clever about pruning before I'd even confirmed the basic approach worked.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by clarifying the problem and edge cases, then propose a bitmask-based backtracking solution that explores all subsets while pruning invalid concatenations. Discuss time/space complexity and potential optimizations like memoization or DP over masks.

Pro tip: Mention that you can preprocess each string to check for duplicate characters and compute its bitmask, which speeds up the backtracking and shows attention to practical optimization.

1. Clarify the problem

Ask questions to confirm constraints: Are all strings lowercase? Can we choose any subset? Is the empty subset allowed? What should be returned if no valid concatenation exists?

2. Preprocess strings

For each string, check if it has duplicate characters; if so, discard it. Otherwise, compute a 26-bit mask representing its characters.

3. Design the algorithm

Use backtracking to explore subsets, maintaining a combined mask. For each string, if its mask doesn't overlap with the current mask, include it and recurse. Track the maximum length.

4. Analyze complexity

Explain that the worst-case time complexity is O(2^n * n) due to exploring all subsets, but pruning reduces practical runtime. Space complexity is O(n) for recursion depth.

5. Discuss optimizations

Mention memoization (e.g., DP over masks) or sorting strings by length to potentially find a longer concatenation earlier, though the latter doesn't guarantee optimality.

Key Points to Mention

  • Bitmask representation of character sets for efficient overlap checks
  • Backtracking with pruning to avoid invalid concatenations
  • Time and space complexity analysis
  • Edge cases: empty array, strings with duplicate characters, no valid concatenation
  • Potential optimizations: memoization, sorting by length
  • Trade-offs between different approaches (e.g., brute force vs. DP)

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