"Master Cycle Detection in Undirected Graph (bfs): Take `n` (number) and `edges` (number[][]), execute an optimal problems on bfs/dfs strategy, and return boolean with clean edge-case handling."
Real-World Metaphor:
Think of Cycle Detection in Undirected Graph (bfs) as an everyday real-world challenge: you receive input data, inspect its elements in sequence without making unnecessary duplicate passes, and transform the collection to reach the exact target without wasting computer memory.
Interactive Visual WalkthroughFLOW-DIAGRAM
Step 1 / 3
StatusInitialized
ModeScanning
Evaluating
1. Initialize State for Cycle Detection in Undirected Graph (bfs)
Load inputs and initialize algorithmic registers.
How to Think About This (Mental Model)
Unpack the problem parameters (`n` (number) and `edges` (number[][])) and clarify what is given vs what must be returned.
Identify the optimal data structure or pattern (e.g. pointers, hash map, or stack) to avoid redundant recalculations.
Walk through state transitions, handle edge cases (empty collections, single items, negative numbers), and return the verified result.
Given `n` nodes and an edge list `edges` representing a network graph, determine the solution for **Cycle Detection in Undirected Graph (bfs)**.
Identify connected components, cycles, or shortest paths.
Examples
Example 1
Input: n = 4, edges = [[0,1],[1,2],[2,3]]
Output: true
Constraints
1 <= n <= 2000
0 <= edges.length <= 5000
Topic Tags:
Graphs [Concepts & Problems]Problems on BFS/DFScycleDetectionInUndirectedGraphBfs