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Oracle·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Oracle SWE interview, pretty standard algorithmic round. One question, backtracking, nothing that'll surprise you if you've done any prep.

Questions Asked (1)

Q1

Given an array of distinct integers, write a function that returns all possible permutations of those integers.

Algorithms & Data Structures
Author's notes

Classic backtracking problem.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem constraints (e.g., array size, distinctness) and then explain a backtracking approach that builds permutations by swapping elements in-place. Walk through a small example to illustrate the recursion and discuss time/space complexity.

Pro tip: Mention that swapping avoids extra space for a 'used' array and that the algorithm generates permutations in-place, but be careful to swap back to maintain correctness. Also, note that for very large n, generating all permutations is impractical due to factorial time, so clarify if the interviewer expects an optimized approach for large inputs.

1. Clarify requirements and constraints

Ask about input size, whether the array can be modified, and if the output should be in a specific order. Confirm that all integers are distinct.

2. Choose an approach

Decide between backtracking with a 'used' array or in-place swapping. Explain that swapping is more space-efficient (O(1) extra space) but modifies the input.

3. Outline the recursive algorithm

Describe the base case (when the current index reaches the end, add a copy of the permutation to the result) and the recursive step (swap the current element with each subsequent element, recurse, then swap back).

4. Analyze complexity

State that there are n! permutations, each of length n, so time complexity is O(n * n!) and space complexity is O(n) for recursion stack (plus output storage).

5. Test with an example

Walk through a small array like [1,2,3] to demonstrate how the swaps generate all permutations and ensure no duplicates are produced.

Key Points to Mention

  • Backtracking as the core technique
  • In-place swapping to avoid extra space for tracking used elements
  • Time complexity: O(n * n!) and space complexity: O(n) for recursion
  • Handling of distinct integers ensures no duplicate permutations
  • Recursion base case and the need to copy the permutation when adding to results
  • Potential optimization: iterative approach or Heap's algorithm for fewer swaps

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