Knew this one cold so I jumped straight to backtracking with a visited set.
Start by clarifying the problem constraints (e.g., array size, distinct integers) and then present a backtracking solution that builds permutations by swapping elements in-place. Discuss time and space complexity, and mention potential optimizations or alternative approaches like Heap's algorithm.
Pro tip: At Apple, interviewers value clean, efficient code and awareness of edge cases; after presenting your solution, briefly discuss how you would test it and handle large inputs, showing production-level thinking.
Ask about input size, whether the array can be empty, and if the output order matters. Confirm that all integers are distinct.
Decide between recursive backtracking (swap-based or used-array) and iterative methods. For interviews, backtracking is usually preferred for clarity.
Explain the recursive structure: at each index, swap the current element with each subsequent element, recurse, then backtrack. Base case: when index reaches end, add permutation to result.
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 (excluding output).
Mention handling empty array (return empty list), single element, and potential optimizations like Heap's algorithm for fewer swaps or iterative solutions to avoid recursion overhead.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.