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Snapchat·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Snapchat SWE interview with a card-flipping string formation problem. Pretty niche problem, not your typical LeetCode grind fare, and the backtracking angle took me a minute to see clearly.

Questions Asked (1)

Q1

You're given a set of cards where each card has a letter on each side. Given a target string, can you form it using the cards, where each card can only contribute one of its two letters and each card can only be used once?

Algorithms & Data Structures
Author's notes

I stared at this for a bit before the constraint clicked: if 'a' and 'b' are on the same card, you can't use both.

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AI HintsAI Generated

Suggested Approach

Model the problem as a bipartite matching or flow problem where cards are matched to characters in the target string. Use backtracking with pruning or maximum bipartite matching to determine if a valid assignment exists. Discuss time/space complexity and potential optimizations.

Pro tip: Clarify constraints upfront (e.g., target length vs. number of cards, duplicate letters) to choose the right algorithm. Mention that if each card can be used at most once and each character needs a distinct card, it's a matching problem, not just a frequency count.

1. Clarify the problem

Ask about constraints: Can cards be reused? Are there duplicate letters? What are the input sizes? Confirm that each card can contribute at most one letter and each card can be used only once.

2. Model as matching

Represent each card as a node with two possible letters, and each character in the target string as a demand. This is a bipartite matching problem between cards and target positions.

3. Choose an algorithm

For small inputs, use backtracking with pruning (e.g., sort cards by flexibility). For larger inputs, use maximum bipartite matching (Hopcroft-Karp) or max flow.

4. Analyze complexity

State the time and space complexity of your approach. For matching, it's O(E√V) where V is cards + target length, E is edges (at most 2 per card).

5. Test and optimize

Walk through edge cases (e.g., target longer than cards, duplicate letters). Discuss optimizations like early termination or greedy heuristics if applicable.

Key Points to Mention

  • Bipartite matching formulation
  • Backtracking with pruning for small inputs
  • Maximum matching algorithms (Hopcroft-Karp, Ford-Fulkerson)
  • Time and space complexity analysis
  • Edge cases: duplicate letters, insufficient cards, target length
  • Potential greedy approach and why it may fail

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