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This composite question evaluates dynamic programming and algorithmic optimization via the triangle minimum path problem and probability, stopping-time analysis and Monte Carlo simulation through the two-dice experiment, testing competencies in DP, discrete probability, expected-value reasoning and empirical estimation.

  • nan
  • Agoda
  • Coding & Algorithms
  • Software Engineer

Compute triangle min path and dice stopping stats

Company: Agoda

Role: Software Engineer

Category: Coding & Algorithms

Difficulty: nan

Interview Round: Technical Screen

You are given two independent interview questions. ## 1) Triangle minimum path sum (DP) Given a triangular array `triangle` with `n` rows, find the minimum path sum from the top to the bottom. - You start at `triangle[0][0]`. - From row `i`, column `j`, you may move to row `i+1` at column `j` or `j+1`. - Return the minimum possible sum along any valid top-to-bottom path. **Input:** A list of lists, where row `i` has length `i+1`. **Output:** An integer (or numeric) minimum path sum. **Constraints (typical):** `1 <= n <= 2000`, values may be negative/positive. --- ## 2) Two dice stopping problem + Monte Carlo There are two fair dice: - Die A has faces `{1,2,3,4,5}` (a 5-sided die). - Die B has faces `{1,2,3,4,5,6}` (a 6-sided die). The experiment proceeds in **rounds**. In each round, you roll **both** dice once. - The process **stops** at the first round where **at least one** die shows `1`. - In the stopping round: - Die A **wins** if `A=1` and `B≠1`. - Die B **wins** if `B=1` and `A≠1`. - It is a **tie** if `A=1` and `B=1`. Answer the following: 1. What is the probability that the **5-sided die (Die A) wins**? 2. What is the **expected number of rounds** until the process stops? 3. Implement a **Monte Carlo simulation** to estimate (1) and (2), and discuss how many trials you would run to get a stable estimate.

Quick Answer: This composite question evaluates dynamic programming and algorithmic optimization via the triangle minimum path problem and probability, stopping-time analysis and Monte Carlo simulation through the two-dice experiment, testing competencies in DP, discrete probability, expected-value reasoning and empirical estimation.

Triangle Minimum Path Sum

Return the minimum top-to-bottom path sum in a triangular array.

Constraints

  • row i has length i + 1

Examples

Input: ([[2], [3, 4], [6, 5, 7], [4, 1, 8, 3]],)

Expected Output: 11

Explanation: Classic example.

Input: ([[-10]],)

Expected Output: -10

Explanation: Single negative row.

Input: ([],)

Expected Output: 0

Explanation: Empty triangle.

Input: ([[1], [2, 3]],)

Expected Output: 3

Explanation: Two rows.

Hints

  1. Fold the DP from the bottom row upward.

Two Dice Stopping Statistics

Return the probability that the 5-sided die wins and the expected number of rounds until at least one die shows 1.

Constraints

  • Die A has faces 1..5; Die B has faces 1..6

Examples

Input: ()

Expected Output: (0.5, 3.0)

Explanation: Analytical probability and expectation.

Hints

  1. Condition on the first stopping round.
Last updated: Jun 27, 2026

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  • Find two numbers that sum to a target - Agoda (nan)

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