How do you solve Minimum Swaps to Avoid Forbidden Values on LeetCode?

Minimum Swaps to Avoid Forbidden Values (LeetCode #3785) 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: Count occurrences to identify swaps needed.

What is the time complexity of Minimum Swaps to Avoid Forbidden Values?

The optimal solution for Minimum Swaps to Avoid Forbidden Values runs in O(n) time and uses O(n) space. This complexity is linear since we only traverse the arrays a couple of times.

What is the brute force solution for Minimum Swaps to Avoid Forbidden Values?

The brute force approach for Minimum Swaps to Avoid Forbidden Values is Brute Force, with O(n²) time complexity and O(1) space complexity. Try all possible swaps to check if we can avoid forbidden values. This is inefficient as it checks every combination. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Minimum Swaps to Avoid Forbidden Values?

Minimum Swaps to Avoid Forbidden Values uses the following concepts: Array, Hash Table, Greedy, Counting. The recommended patterns to study are: Hash Map, Array.

What are the interview tips for Minimum Swaps to Avoid Forbidden Values?

Explain your thought process clearly. Use examples to illustrate your approach. Practice coding under time constraints.

What are common mistakes when solving Minimum Swaps to Avoid Forbidden Values?

Overlooking cases where no swaps can resolve conflicts. Not counting all occurrences correctly.

#3785

Minimum Swaps to Avoid Forbidden Values

Hard

ArrayHash TableGreedyCountingHash MapArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

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

💡

Intuition

Time O(n)Space O(n)

Count occurrences of forbidden values and find minimum swaps needed to replace them with non-forbidden values.

⚙️

Algorithm

3 steps

1Step 1: Count frequency of each value in nums and forbidden.
2Step 2: Identify values in nums that match forbidden values and need to be swapped.
3Step 3: Calculate minimum swaps needed to replace forbidden values with non-forbidden values.

solution.py10 lines

1def min_swaps_optimal(nums, forbidden):
2    from collections import Counter
3    freq = Counter(nums)
4    forbidden_count = Counter(forbidden)
5    swaps = 0
6    for num in forbidden:
7        if freq[num] > 0:
8            swaps += 1
9            freq[num] -= 1
10    return swaps if swaps <= len(nums) else -1

ℹ

Complexity note: This complexity is linear since we only traverse the arrays a couple of times.

1Count occurrences to identify swaps needed.
2Focus on replacing forbidden values with alternatives.

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