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Bytedance·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Bytedance software engineer coding round, pretty standard algorithms stuff but they pushed on complexity and wanted you to know more than one approach.

Questions Asked (1)

Q1

Given an array of unique integers, return all possible subsets (the power set) with no duplicate subsets.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

I went straight to backtracking, include or exclude at each step and emit the current subset at every node.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem constraints (e.g., array size, uniqueness) and then present a backtracking solution that builds subsets incrementally. Explain the decision tree and how you avoid duplicates by only considering elements after the current index. Optionally, mention iterative or bit manipulation approaches as alternatives.

Pro tip: After presenting the solution, discuss the time complexity (O(2^n)) and space complexity (O(n) for recursion stack), and mention that the output size itself is exponential, so it's optimal. Also, highlight how you would handle large inputs or memory constraints in a real interview.

1. Clarify the problem

Ask about input size, uniqueness, and whether the output order matters. Confirm that the array contains unique integers and that subsets should be unique.

2. Choose an approach

Decide between backtracking, iterative, or bit manipulation. Backtracking is intuitive and easy to explain; iterative is concise; bit manipulation is clever but less readable.

3. Explain the algorithm

Walk through the chosen approach step-by-step. For backtracking, describe how you recursively include/exclude each element, starting from a given index to avoid duplicates.

4. Analyze complexity

State that the time complexity is O(n * 2^n) because there are 2^n subsets and each takes O(n) to copy. Space complexity is O(n) for recursion stack, excluding output.

5. Discuss trade-offs and edge cases

Mention alternative approaches and their pros/cons. Handle edge cases like empty array (return [[]]) and large n (memory considerations).

Key Points to Mention

  • Backtracking with recursion and a start index to avoid duplicates
  • Time complexity: O(n * 2^n) due to generating all subsets and copying them
  • Space complexity: O(n) for recursion stack (excluding output)
  • Iterative approach: start with [[]] and for each number, add it to all existing subsets
  • Bit manipulation: use bits 0 to 2^n - 1 to represent subsets
  • Edge cases: empty array returns [[]], large n may cause memory issues

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