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HomeLeetCode ProblemsMaximum Profit from Valid Topological Order in DAG
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How to Solve Maximum Profit from Valid Topological Order in DAG Problem

Master the Maximum Profit from Valid Topological Order in DAG LeetCode problem with undetectable real-time assistance. Get instant solutions and explanations during your coding interviews.

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Hard#3530
LeetCode Problem

Maximum Profit from Valid Topological Order in DAG

You are given a Directed Acyclic Graph (DAG) with n nodes labeled from 0 to n - 1, represented by a 2D array edges, where edges[i] = [ui, vi] indicates a directed edge from node ui to vi. Each node has an associated score given in an array score, where score[i] represents the score of node i. You must process the nodes in a valid topological order. Each node is assigned a 1-based position in the processing order. The profit is calculated by summing up the product of each node's score and its position in the ordering. Return the maximum possible profit achievable with an optimal topological order. A topological order of a DAG is a linear ordering of its nodes such that for every directed edge u → v, node u comes before v in the ordering.

ArrayDynamic ProgrammingBit ManipulationGraphTopological SortBitmask

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Problem Breakdown

Understanding the Maximum Profit from Valid Topological Order in DAG Problem

Let's break down this LeetCode problem and understand what makes it challenging in interview settings.

Problem Statement

You are given a Directed Acyclic Graph (DAG) with n nodes labeled from 0 to n - 1, represented by a 2D array edges, where edges[i] = [ui, vi] indicates a directed edge from node ui to vi. Each node has an associated score given in an array score, where score[i] represents the score of node i. You must process the nodes in a valid topological order. Each node is assigned a 1-based position in the processing order. The profit is calculated by summing up the product of each node's score and its position in the ordering. Return the maximum possible profit achievable with an optimal topological order. A topological order of a DAG is a linear ordering of its nodes such that for every directed edge u → v, node u comes before v in the ordering.

HardProblem #3530
LeetCode

Maximum Profit from Valid Topological Order in DAG

Related Topics

ArrayDynamic ProgrammingBit ManipulationGraphTopological SortBitmask

How Phantom Code Helps

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Examples

# Example 1

Input
n = 2, edges = [[0,1]], score = [2,3]
Output
8

# Example 2

Input
n = 3, edges = [[0,1],[0,2]], score = [1,6,3]
Output
25

Constraints

1 <= n == score.length <= 22
1 <= score[i] <= 105
0 <= edges.length <= n * (n - 1) / 2
edges[i] == [ui, vi] denotes a directed edge from ui to vi.
0 <= ui, vi < n
ui != vi
The input graph is guaranteed to be a DAG.
There are no duplicate edges.

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Solve Maximum Profit from Valid Topological Order in DAG — You are given a Directed Acyclic Graph (DAG) with n nodes labeled from 0 to n - ...

Here's the optimal approach using Array:

def solve(input):
# Optimal O(n) solution
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Frequently Asked Questions

Common questions about solving Maximum Profit from Valid Topological Order in DAG and using Phantom Code during coding interviews.

How does Phantom Code help me solve coding problems like Maximum Profit from Valid Topological Order in DAG 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 Maximum Profit from Valid Topological Order in DAG?
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 Maximum Profit from Valid Topological Order in DAG?
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 Maximum Profit from Valid Topological Order in DAG 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 Maximum Profit from Valid Topological Order in DAG 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 Maximum Profit from Valid Topological Order in DAG 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 Maximum Profit from Valid Topological Order in DAG 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 Maximum Profit from Valid Topological Order in DAG 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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