1p3a_oj Question

Maximize Rice Units Taken Without Emptying Piles Using DP

SWE coding 0

Question Details

Use dynamic programming to solve the following problem: You have an integer array where each element represents the initial units of rice in a pile. You can start from any pile, and at each step, choo

Full Details

Use dynamic programming to solve the following problem: You have an integer array where each element represents the initial units of rice in a pile. You can start from any pile, and at each step, choose to take any number of rice units from the current pile, but not more than the remaining units in that pile. Simultaneously, you may choose to move to an adjacent pile or end your action. The goal is to maximize the total units of rice taken without emptying any pile completely. Given an integer array piles representing the amount of rice in each pile, find the maximum rice units that can be taken.

Example:

Input: piles = [3, 4, 5, 1, 2]

Output: 9

Constraints:

  • 1 <= piles.length <= 10^4
  • 1 <= piles[i] <= 1000

Sample Input

3 4 5 1 2
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About This Question

This is a reported interview question from a openai interview for a swe role during the coding round.

It covers the following topics: Arrays, Dynamic Programming .

Difficulty rating: 0

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How To Practice This Type of Question

Solve similar problems on LeetCode under timed conditions (25-35 minutes per medium difficulty). The goal is pattern recognition: recognize the underlying technique (sliding window, two-pointer, BFS, memoized recursion, etc.) within 60-90 seconds of reading. Strong candidates verbalize their hypothesis out loud before coding, then iterate based on feedback. Weak candidates dive into implementation immediately, lose time on the wrong approach, and run out of time for follow-ups.

Companies update their question pools every 2-4 months. The exact wording of any given question may have been retired by the time you interview. Focus your prep on the pattern, not the specific problem. The patterns that appear in OpenAI reports consistently are the ones worth investing in; one-off niche problems are not.

During Your OpenAI Round

Apply the standard interview round template: clarify requirements (2-3 minutes), state your approach out loud and confirm direction with the interviewer (3-5 minutes), code with narration (15-25 minutes), test with concrete examples including edge cases (5 minutes), discuss optimization or trade-offs if time permits (5 minutes). This template is universally accepted across FAANG and adjacent companies; deviating from it produces weaker interviewer feedback signal.

The single most predictive failure mode in OpenAI reports tagged "no hire": not asking clarifying questions. Interviewers are explicitly trained to weight this. Strong candidates ask 3-5 clarifying questions even on problems that look obvious; weak candidates dive into code immediately. The clarifying-question check is often the first signal recorded in the interviewer's written notes.