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How to Solve Count Good Triplets in an Array Problem
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LeetCode ProblemCount Good Triplets in an Array
You are given two 0-indexed arrays nums1 and nums2 of length n, both of which are permutations of [0, 1, ..., n - 1]. A good triplet is a set of 3 distinct values which are present in increasing order by position both in nums1 and nums2. In other words, if we consider pos1v as the index of the value v in nums1 and pos2v as the index of the value v in nums2, then a good triplet will be a set (x, y, z) where 0 <= x, y, z <= n - 1, such that pos1x < pos1y < pos1z and pos2x < pos2y < pos2z. Return the total number of good triplets.
ArrayBinary SearchDivide and ConquerBinary Indexed TreeSegment TreeMerge SortOrdered Set
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Problem Breakdown
Understanding the Count Good Triplets in an Array Problem
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Problem Statement
You are given two 0-indexed arrays nums1 and nums2 of length n, both of which are permutations of [0, 1, ..., n - 1]. A good triplet is a set of 3 distinct values which are present in increasing order by position both in nums1 and nums2. In other words, if we consider pos1v as the index of the value v in nums1 and pos2v as the index of the value v in nums2, then a good triplet will be a set (x, y, z) where 0 <= x, y, z <= n - 1, such that pos1x < pos1y < pos1z and pos2x < pos2y < pos2z. Return the total number of good triplets.
HardProblem #2179
LeetCodeCount Good Triplets in an Array
Related Topics
ArrayBinary SearchDivide and ConquerBinary Indexed TreeSegment TreeMerge SortOrdered Set
How Phantom Code Helps
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Examples
# Example 1
Input
nums1 = [2,0,1,3], nums2 = [0,1,2,3]
Output
1
# Example 2
Input
nums1 = [4,0,1,3,2], nums2 = [4,1,0,2,3]
Output
4
Constraints
n == nums1.length == nums2.length
3 <= n <= 105
0 <= nums1[i], nums2[i] <= n - 1
nums1 and nums2 are permutations of [0, 1, ..., n - 1].
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Solve Count Good Triplets in an Array — You are given two 0-indexed arrays nums1 and nums2 of length n, both of which ar...
Here's the optimal approach using Array:
def solve(input):
# Optimal O(n) solution
return result
Time: O(n) | Space: O(n)
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Frequently Asked Questions
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Phantom Code generates complete solutions instantly with proper complexity analysis, letting you focus on explaining your approach and demonstrating problem-solving skills rather than getting stuck on implementation details during high-pressure situations.
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Phantom Code catches common mistakes like off-by-one errors, missing edge cases, incorrect base conditions, and suboptimal approaches. It provides clean, well-structured code that handles all edge cases.
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The AI provides structured guidance: first the approach (what algorithm/data structure to use and why), then the implementation with clean code, and finally complexity analysis. This helps you think clearly even under pressure.
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