I went with backtracking, include or exclude each element as you recurse down.
Start by clarifying the problem constraints and edge cases, then present a backtracking solution that builds subsets incrementally. Discuss the time and space complexity, and mention alternative approaches like bit manipulation for comparison.
Pro tip: Demonstrate strong communication by walking through a small example step-by-step before coding, and proactively discuss trade-offs between recursive and iterative solutions. This shows you think about maintainability and performance, which is highly valued at Google.
Ask about input size, uniqueness, and expected output format to ensure alignment with the interviewer.
Explain the backtracking strategy: start with an empty subset, and for each element, decide to include or exclude it, recursively building all subsets.
Trace the algorithm on a small array (e.g., [1,2]) to illustrate how subsets are generated and avoid duplicates.
State that there are 2^n subsets, each taking O(n) to copy, leading to O(n * 2^n) time and O(n * 2^n) space for the output.
Mention bit manipulation (using binary representation) as an iterative alternative, and note its trade-offs in readability and performance.
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