Problem Statement
Given a reference of a node in a connected undirected graph.
Return a deep copy (clone) of the graph.
Each node in the graph contains a val (int
) and a list (List[Node]
) of its neighbors.
class Node { public int val; public List<Node> neighbors; }
Test case format:
For simplicity sake, each node's value is the same as the node's index (1-indexed). For example, the first node with val = 1
, the second node with val = 2
, and so on. The graph is represented in the test case using an adjacency list.
Adjacency list is a collection of unordered lists used to represent a finite graph. Each list describes the set of neighbors of a node in the graph.
The given node will always be the first node with val = 1
. You must return the copy of the given node as a reference to the cloned graph.
Example 1:
Input: adjList = [[2,4],[1,3],[2,4],[1,3]] Output: [[2,4],[1,3],[2,4],[1,3]] Explanation: There are 4 nodes in the graph. 1st node (val = 1)'s neighbors are 2nd node (val = 2) and 4th node (val = 4). 2nd node (val = 2)'s neighbors are 1st node (val = 1) and 3rd node (val = 3). 3rd node (val = 3)'s neighbors are 2nd node (val = 2) and 4th node (val = 4). 4th node (val = 4)'s neighbors are 1st node (val = 1) and 3rd node (val = 3).
Example 2:
Input: adjList = [[]] Output: [[]] Explanation: Note that the input contains one empty list. The graph consists of only one node with val = 1 and it does not have any neighbors.
Example 3:
Input: adjList = [] Output: [] Explanation: This an empty graph, it does not have any nodes.
Example 4:
Input: adjList = [[2],[1]] Output: [[2],[1]]
Constraints:
1 <= Node.val <= 100
Node.val
is unique for each node.- Number of Nodes will not exceed 100.
- There is no repeated edges and no self-loops in the graph.
- The Graph is connected and all nodes can be visited starting from the given node.
Video Tutorial
You can find the detailed video tutorial hereThought Process
It's a basic graph problem that can be solved in 3 different ways: BFS using queue, DFS using recursion, DFS using stack(very similar to BFT using queue). The trick is using a map to keep a one-to-one mapping between the old nodes and the copied nodes, meanwhile, we can also use the map to avoid a cycle when performing BFS or DFS.Solutions
BFS using queue
Time Complexity: O(N)Space Complexity: O(N) the extra queue and map
DFS using recursion
Time Complexity: O(N) Space Complexity: O(N) the extra map
DFS using stack
Time Complexity: O(N) Space Complexity: O(N) the extra queue and stack
The main test method
References
- Leetcode official solution (download pdf)
- Code Ganker CSDN