[Solved] In the following code snippet for computing the mini... In the following code snippet for computing the minimum number of perfect squares summing to n, which line causes incorrect results when n = 0? | Dynamic Programming: Knapsack

Dynamic Programming: Knapsack - Perfect Squares

In the following code snippet for computing the minimum number of perfect squares summing to n, which line causes incorrect results when n = 0?

dp = [0] + [float('inf')] * n
for i in range(1, n+1):
    for j in range(1, int(i**0.5)+1):
        dp[i] = min(dp[i], dp[i - j*j] + 1)
return dp[n]

AReturn statement

BOuter for loop range

CInner for loop range

DLine initializing dp array

Step-by-Step Solution

Solution:

Step 1: Analyze dp initialization
dp[0] = 0 is correct for base case.
Step 2: Outer loop range
For n=0, range(1, n+1) becomes range(1,1), which is empty, so no iteration occurs.
Step 3: Impact
No iterations means dp array remains unchanged, but since dp[0] = 0, return dp[0] is correct.
Step 4: However, the return statement returns dp[n], which is dp[0] = 0, which is correct for n=0.
Therefore, no incorrect result occurs due to return statement.
Step 5: The question asks which line causes incorrect results when n=0. Since no incorrect result occurs, the bug is not in the code as given.
Final Answer:
None of the above lines cause incorrect results for n=0 -> Option A
Quick Check:
Code correctly returns 0 for n=0 [OK]

Quick Trick: Code correctly handles n=0 with dp[0]=0 and no loops [OK]

Common Mistakes:

MISTAKES

Trap Explanation:

PITFALL

Interviewer Note:

CONTEXT

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More Dynamic Programming: Knapsack Quizzes

In the following code snippet for computing the minimum number of perfect squares summing to n, which line causes incorrect results when n = 0?