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Confluent·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Confluent SWE interview with a permutation/subset-sum problem dressed up as a warehouse robot scenario. Took me a minute to see past the story and recognize what was actually being asked.

Questions Asked (1)

Q1

You have a robot that starts at load 0 and processes N integer operations (positive to load, negative to unload). The order of operations is unknown. Can you determine whether any ordering of these operations produces a running total equal to a given target weight at some point during processing?

Algorithms & Data Structures
Author's notes

Took me longer than it should have to strip away the robot framing and see this as a subset-sum reachability problem.

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AI HintsAI Generated

Suggested Approach

Model the problem as a reachability question over possible running sums, using a set to track all achievable totals after each operation. Since the order is unknown, consider all permutations, but optimize by recognizing that the set of reachable sums after processing a subset of operations depends only on which operations are included, not their order. Use dynamic programming or BFS over subsets to determine if the target is reachable.

Pro tip: Clarify whether operations can be reordered arbitrarily or if some constraints exist; if arbitrary, the problem reduces to subset sum with signs, which is NP-hard in general. Mention that for small N, brute force is fine, but for large N, you need to discuss complexity and potential approximations.

1. Understand the problem

Restate the problem: given N integers (positive/negative), can we order them so that at some point the running sum equals the target? Note that the running sum starts at 0 and changes by each operation.

2. Identify the core computational challenge

Recognize that the order matters only in that we can choose any permutation. The set of possible running sums after k operations is the set of sums of any k-element subset of the operations, but with signs as given. This is equivalent to: does there exist a subset of operations whose sum equals the target, and can that subset be placed first in some order? Actually, any subset can be placed first, so the problem reduces to: is there a subset of the operations whose sum equals the target?

3. Reduce to subset sum

Since we can order operations arbitrarily, we can choose any subset to be the first k operations. The running sum after those k operations is the sum of that subset. Thus, the question becomes: does any subset of the given integers sum to the target? This is the classic subset sum problem.

4. Discuss solution approaches and complexity

For small N, use brute force or dynamic programming (pseudo-polynomial). For large N, note that subset sum is NP-complete, so no polynomial-time solution is known. Mention possible optimizations like meet-in-the-middle for N up to ~40, or DP if the target is small.

5. Consider edge cases and constraints

Handle cases like target=0 (empty subset always works), all positive/negative numbers, and large values. Clarify if N is small enough for exponential algorithms or if approximation is acceptable.

Key Points to Mention

  • The problem reduces to subset sum because any subset can be ordered first.
  • Subset sum is NP-complete, so no known polynomial-time algorithm for arbitrary N.
  • Dynamic programming works in O(N * sum) time, which is pseudo-polynomial.
  • Meet-in-the-middle can solve N up to about 40 in O(2^(N/2)) time.
  • Edge case: target 0 is always achievable by taking no operations.
  • Clarify constraints: if N is small, brute force is acceptable; if large, discuss complexity.

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