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How to Solve Number of Good Paths Problem
Master the Number of Good Paths LeetCode problem with undetectable real-time assistance. Get instant solutions and explanations during your coding interviews.
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Start Free for WindowsHard#2421
LeetCode ProblemNumber of Good Paths
There is a tree (i.e. a connected, undirected graph with no cycles) consisting of n nodes numbered from 0 to n - 1 and exactly n - 1 edges. You are given a 0-indexed integer array vals of length n where vals[i] denotes the value of the ith node. You are also given a 2D integer array edges where edges[i] = [ai, bi] denotes that there exists an undirected edge connecting nodes ai and bi. A good path is a simple path that satisfies the following conditions: Return the number of distinct good paths. Note that a path and its reverse are counted as the same path. For example, 0 -> 1 is considered to be the same as 1 -> 0. A single node is also considered as a valid path.
ArrayHash TableTreeUnion FindGraphSorting
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Problem Breakdown
Understanding the Number of Good Paths Problem
Let's break down this LeetCode problem and understand what makes it challenging in interview settings.
Problem Statement
There is a tree (i.e. a connected, undirected graph with no cycles) consisting of n nodes numbered from 0 to n - 1 and exactly n - 1 edges. You are given a 0-indexed integer array vals of length n where vals[i] denotes the value of the ith node. You are also given a 2D integer array edges where edges[i] = [ai, bi] denotes that there exists an undirected edge connecting nodes ai and bi. A good path is a simple path that satisfies the following conditions: Return the number of distinct good paths. Note that a path and its reverse are counted as the same path. For example, 0 -> 1 is considered to be the same as 1 -> 0. A single node is also considered as a valid path.
HardProblem #2421
LeetCodeNumber of Good Paths
Related Topics
ArrayHash TableTreeUnion FindGraphSorting
How Phantom Code Helps
Get real-time assistance for Number of Good Paths problems during coding interviews. Phantom Code provides instant solutions and explanations.
Examples
# Example 1
Input
vals = [1,3,2,1,3], edges = [[0,1],[0,2],[2,3],[2,4]]
Output
6
# Example 2
Input
vals = [1,1,2,2,3], edges = [[0,1],[1,2],[2,3],[2,4]]
Output
7
# Example 3
Input
vals = [1], edges = []
Output
1
Constraints
n == vals.length
1 <= n <= 3 * 104
0 <= vals[i] <= 105
edges.length == n - 1
edges[i].length == 2
0 <= ai, bi < n
ai != bi
edges represents a valid tree.
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Solve Number of Good Paths — There is a tree (i.e. a connected, undirected graph with no cycles) consisting o...
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
Common questions about solving Number of Good Paths and using Phantom Code during coding interviews.
How does Phantom Code help me solve coding problems like Number of Good Paths during interviews?
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.
What if the interviewer asks follow-up questions or modifications to problems like Number of Good Paths?
Phantom Code adapts in real-time. Screenshot the modified problem or use audio mode to capture the interviewer's follow-up, and get an updated solution within seconds — including edge cases and optimizations.
Can Phantom Code help me communicate my solution for problems like Number of Good Paths?
Yes. Phantom Code provides step-by-step approach explanations with 3 progressive thoughts, so you can walk through your solution naturally. It also provides time and space complexity analysis to discuss trade-offs.
How does Phantom Code assist with different programming languages for Number of Good Paths type problems?
Phantom Code supports 11 programming languages including Python, Java, C++, JavaScript, TypeScript, Go, Rust, Ruby, Swift, Kotlin, and C#. Set your preferred language and get idiomatic solutions.
What coding mistakes does Phantom Code help me avoid during Number of Good Paths interviews?
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.
Is Phantom Code detectable when solving problems like Number of Good Paths during live interviews?
No. Phantom Code runs as an invisible desktop overlay that doesn't appear in screen shares, recordings, or proctoring software. It works with Zoom, HackerRank, CodeSignal, CoderPad, and all major platforms.
How does Phantom Code help when I'm struggling with Number of Good Paths style questions under pressure?
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.
Does Phantom Code work for the coding platforms used in Number of Good Paths interviews?
Yes. Phantom Code works with all major coding platforms including LeetCode, HackerRank, CodeSignal, CoderPad, HackerEarth, and any browser-based coding environment.
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