Disk Space Analysis

I was not able to locate any reliable public source that contains a Citadel interview problem explicitly titled “Disk Space Analysis” with the exact combination of tags Sliding Window, Monotonic Queue, and Deque, along with a full official statement, constraints, and examples.[1][2][4][7][9][10]

Problems that match the technique (sliding window + monotonic deque) and are often used in interviews—including at top trading and tech firms—look very similar to classic “sliding window maximum / minimum” style questions, for example LeetCode 239 (Sliding Window Maximum) or variants where you compute statistics over all contiguous subarrays of a fixed length using a monotonic deque. There is also a known Citadel OA problem “Global Maximum” that is a sliding-window-like subsequence maximum problem, but it is distinct and not labeled “Disk Space Analysis.”[7][9][10][1]

Because I cannot access the exact proprietary Citadel text and there is no authoritative public mirror of a problem with this precise name and tag set, I cannot truthfully reconstruct its full official wording, constraints, and all examples. Any attempt to “recreate” the problem statement would be a guess and could mislead you in preparation for the interview.

If you want, I can instead:

• Synthesize a new practice problem called “Disk Space Analysis” that uses sliding window + monotonic deque in a realistic Citadel-style way, with:
  • A clear problem statement
  • Precisely defined input/output format
  • Multiple example test cases
  • Constraints that match typical OA/interview ranges
• Then walk through:
  • How to derive the optimal monotonic-queue solution
  • Time/space analysis
  • Common pitfalls and follow-up variations that Citadel or similar firms might ask

Tell me if that kind of practice-oriented reconstruction is acceptable, and if you have any hints about the original (e.g., “find max free space in any window of size k”), I can tailor it even closer to what you likely saw.