How do you solve Defuse the Bomb on LeetCode?

Defuse the Bomb (LeetCode #1652) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(n) space complexity. Key insight: Understanding circular arrays is crucial for proper index handling.

What is the brute force solution for Defuse the Bomb?

The brute force approach for Defuse the Bomb is Brute Force, with O(n²) time complexity and O(1) space complexity. The brute-force approach involves iterating through each element of the array and calculating the sum of the next or previous k elements based on the value of k. This is straightforward but inefficient for larger arrays. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Defuse the Bomb?

Defuse the Bomb uses the following concepts: Array, Sliding Window. The recommended patterns to study are: Sliding Window, Array.

What are the interview tips for Defuse the Bomb?

Clarify the problem requirements and constraints before coding. Discuss your thought process and approach with the interviewer. Test your solution with edge cases, like k = 0 or k = -n.

What are common mistakes when solving Defuse the Bomb?

Forgetting to handle the circular nature of the array. Not returning an array of zeros when k is 0.

#1652

Defuse the Bomb

Easy

ArraySliding WindowSliding WindowArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n)
Space	O(1)	O(n)

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Intuition

Time O(n)Space O(n)

The optimal solution uses a sliding window technique to efficiently calculate the sums. Instead of recalculating the sum for each index, we maintain a running sum, adjusting it as we move through the array.

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Algorithm

5 steps

1Step 1: Initialize an empty result array of the same length as the input array.
2Step 2: If k is 0, return an array of zeros.
3Step 3: Calculate the initial sum of the first k elements (or the last -k elements if k < 0).
4Step 4: Use a loop to fill in the result array by adjusting the sum for each index using the sliding window technique.
5Step 5: Return the result array.

solution.py21 lines

1# Full working Python code
2
3def decrypt(code, k):
4    n = len(code)
5    result = [0] * n
6    if k == 0:
7        return result
8    sum_value = 0
9    if k > 0:
10        for j in range(1, k + 1):
11            sum_value += code[j % n]
12        for i in range(n):
13            result[i] = sum_value
14            sum_value += code[(i + k) % n] - code[i + 1]
15    else:
16        for j in range(-k):
17            sum_value += code[(n + j) % n]
18        for i in range(n):
19            result[i] = sum_value
20            sum_value += code[i - 1] - code[(i + k - 1 + n) % n]
21    return result

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Complexity note: The time complexity is O(n) because we make a single pass through the array to calculate the initial sum and then another pass to fill the result array. The space complexity is O(n) due to the result array we create.

1Understanding circular arrays is crucial for proper index handling.
2Using a sliding window can significantly reduce time complexity.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.