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How to Solve Path with Maximum Probability Problem
Master the Path with Maximum Probability LeetCode problem with undetectable real-time assistance. Get instant solutions and explanations during your coding interviews.
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Start Free for WindowsMedium#1514
LeetCode ProblemPath with Maximum Probability
You are given an undirected weighted graph of n nodes (0-indexed), represented by an edge list where edges[i] = [a, b] is an undirected edge connecting the nodes a and b with a probability of success of traversing that edge succProb[i]. Given two nodes start and end, find the path with the maximum probability of success to go from start to end and return its success probability. If there is no path from start to end, return 0. Your answer will be accepted if it differs from the correct answer by at most 1e-5.
ArrayGraphHeap (Priority Queue)Shortest Path
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Problem Breakdown
Understanding the Path with Maximum Probability Problem
Let's break down this LeetCode problem and understand what makes it challenging in interview settings.
Problem Statement
You are given an undirected weighted graph of n nodes (0-indexed), represented by an edge list where edges[i] = [a, b] is an undirected edge connecting the nodes a and b with a probability of success of traversing that edge succProb[i]. Given two nodes start and end, find the path with the maximum probability of success to go from start to end and return its success probability. If there is no path from start to end, return 0. Your answer will be accepted if it differs from the correct answer by at most 1e-5.
MediumProblem #1514
LeetCodePath with Maximum Probability
Related Topics
ArrayGraphHeap (Priority Queue)Shortest Path
How Phantom Code Helps
Get real-time assistance for Path with Maximum Probability problems during coding interviews. Phantom Code provides instant solutions and explanations.
Examples
# Example 1
Input
n = 3, edges = [[0,1],[1,2],[0,2]], succProb = [0.5,0.5,0.2], start = 0, end = 2
Output
0.25000
# Example 2
Input
n = 3, edges = [[0,1],[1,2],[0,2]], succProb = [0.5,0.5,0.3], start = 0, end = 2
Output
0.30000
# Example 3
Input
n = 3, edges = [[0,1]], succProb = [0.5], start = 0, end = 2
Output
0.00000
Constraints
2 <= n <= 10^4
0 <= start, end < n
start != end
0 <= a, b < n
a != b
0 <= succProb.length == edges.length <= 2*10^4
0 <= succProb[i] <= 1
There is at most one edge between every two nodes.
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Solve Path with Maximum Probability — You are given an undirected weighted graph of n nodes (0-indexed), represented b...
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 Path with Maximum Probability and using Phantom Code during coding interviews.
How does Phantom Code help me solve coding problems like Path with Maximum Probability 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 Path with Maximum Probability?
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 Path with Maximum Probability?
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 Path with Maximum Probability 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 Path with Maximum Probability 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 Path with Maximum Probability 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 Path with Maximum Probability 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 Path with Maximum Probability 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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