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Xai·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Got a coding question from xAI that was basically the combination sum variant where each element can only be used once. Pretty standard backtracking problem but the duplicate handling trips people up if you haven't seen it.

Questions Asked (1)

Q1

Given a list of candidate numbers and a target, find all unique combinations that sum to the target, where each number can only be used once.

Algorithms & Data Structures
Author's notes

The 'no duplicates in the result' constraint is where people slip up.

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AI HintsAI Generated

Suggested Approach

Clarify the problem constraints (e.g., duplicates, negative numbers, target range) and then propose a backtracking solution that sorts the input, skips duplicates at each level, and explores combinations by moving forward. Discuss time and space complexity, and mention potential optimizations like pruning when the current sum exceeds the target.

Pro tip: Demonstrate awareness of the 'combination sum II' pattern: sorting and skipping duplicates at the same recursion depth is crucial to avoid duplicate combinations. Also, explicitly state that each number can be used only once, so the recursive call must advance the index.

1. Clarify constraints and edge cases

Ask about input size, presence of duplicates, negative numbers, and whether the target can be zero. Confirm that each number can be used at most once and that the output should contain unique combinations.

2. Outline the backtracking approach

Explain that you will sort the array to handle duplicates, then use a recursive function that builds combinations, skipping duplicate elements at the same level and pruning when the sum exceeds the target.

3. Detail the recursion and duplicate handling

Describe the recursive calls: at each step, iterate from the current index, skip if the element equals the previous one (to avoid duplicates), include the element, recurse with the next index, and backtrack. Base case: sum equals target.

4. Analyze complexity and optimizations

State the time complexity (exponential in worst case, e.g., O(2^n) or O(n * 2^n)) and space complexity (O(n) for recursion stack). Mention pruning (break when sum > target) and early termination if the smallest element exceeds the remaining target.

5. Test with examples and edge cases

Walk through a small example (e.g., candidates = [10,1,2,7,6,1,5], target = 8) to show how duplicates are skipped and combinations are generated. Discuss edge cases like empty input, no solution, or target smaller than all candidates.

Key Points to Mention

  • Sorting the input to group duplicates and enable pruning
  • Skipping duplicates at the same recursion level (i > start && candidates[i] == candidates[i-1])
  • Using an index to ensure each number is used only once (recursing with i+1)
  • Pruning the search when the current sum exceeds the target
  • Time and space complexity analysis (exponential time, linear space)
  • Handling edge cases: empty list, no combinations, negative numbers, target zero

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