This assessment verifies the Dynamic Programming module. Passing it contributes up to 13 points in the 61-73 score band.
Questions
8
Limit
105m
Pass
85%
Score
+13
13 pts
A pricing engine recursively evaluates discount choices across months. Many branches eventually reach the same `(monthIndex, remainingCredits)` pair and then recompute the same suffix. Explain whether DP applies, define the state, recurrence idea, and what must be included in the memo key.
12 pts
A candidate solves climbing stairs with naive recursion: `ways(n) = ways(n - 1) + ways(n - 2)` and no cache. Review the performance problem, give the memoized or tabulated fix, and state complexity.
15 pts
Design a 0/1 knapsack solution for campaign selection under a fixed budget. Each campaign has cost and value and can be selected at most once. Define `dp[i][b]`, transition, base cases, answer, and complexity.
13 pts
A teammate optimizes subset-sum DP from 2D to 1D and iterates budget from low to high for each number. The problem is 0/1: each number can be used once. Review the bug and correct the iteration order.
13 pts
Given a non-empty grid of non-negative risk values, return the minimum risk path from top-left to bottom-right moving only right or down. Define state, fill order, boundary handling, and complexity.
13 pts
A document comparison feature needs the longest common subsequence length between two strings. A candidate tries to greedily match each character in the first string to the earliest possible character in the second. Explain why greedy is unsafe and define a DP solution.
13 pts
A recommendation planner has millions of theoretical states, but business rules make only a small fraction reachable from a request. Another offline report needs values for every state. Choose memoization or tabulation for each and defend the trade-off.
11 pts
Which answer best demonstrates SkillSkore-level DP reasoning?