How do you solve Find Champion II on LeetCode?

Find Champion II (LeetCode #2924) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n + m) time complexity and O(n) space complexity. Key insight: A champion must have an in-degree of 0 in a DAG.

What is the brute force solution for Find Champion II?

The brute force approach for Find Champion II is Brute Force, with O(n²) time complexity and O(1) space complexity. In the brute force approach, we check each team to see if there is any other team that is stronger than it. If a team has no stronger teams, it could be a champion. This method is straightforward but inefficient. The optimal Optimal Solution approach improves this to O(n + m).

What algorithm or data structure is used to solve Find Champion II?

Find Champion II uses the following concepts: Graph Theory. The recommended patterns to study are: Graph Traversal, Topological Sorting.

What are the interview tips for Find Champion II?

Clearly explain your thought process while solving the problem. Consider edge cases, such as when there are no edges or only one team. Practice explaining your code as if you were teaching someone else.

What are common mistakes when solving Find Champion II?

Not considering the case where multiple teams have in-degree 0. Misunderstanding the definition of in-degree in a directed graph.

#2924

Find Champion II

Medium

Graph TheoryGraph TraversalTopological Sorting

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

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

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Intuition

Time O(n + m)Space O(n)

In the optimal solution, we utilize the property of a Directed Acyclic Graph (DAG) where the champion must have an in-degree of 0. This allows us to efficiently determine the champion by counting incoming edges for each team.

⚙️

Algorithm

4 steps

1Step 1: Initialize an array to count in-degrees for each team.
2Step 2: Iterate through the edges and update the in-degree count for each team.
3Step 3: Identify teams with in-degree 0 and store them in a list.
4Step 4: If there's exactly one team with in-degree 0, return that team; otherwise, return -1.

solution.py6 lines

1def findChampion(n, edges):
2    in_degree = [0] * n
3    for u, v in edges:
4        in_degree[v] += 1
5    champions = [i for i in range(n) if in_degree[i] == 0]
6    return champions[0] if len(champions) == 1 else -1

ℹ

Complexity note: The time complexity is O(n + m) because we traverse all edges and nodes once. The space complexity is O(n) for storing the in-degree counts.

1A champion must have an in-degree of 0 in a DAG.
2If multiple teams have an in-degree of 0, there is no unique champion.

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