797. All Paths From Source to Target
Medium
30 Points
Backtracking
Depth-First Search
Breadth-First Search
Graph
Given a directed acyclic graph (DAG) of n nodes labeled from 0 to n - 1, find all possible paths from node 0 to node n - 1 and return them in any order.
The graph is given as follows: graph[i] is a list of all nodes you can visit from node i (i.e., there is a directed edge from node i to node graph[i][j]).
Examples
Example 1
Input: graph = [[1,2],[3],[3],[]]
Output: [[0,1,3],[0,2,3]]
Explanation: There are two paths: 0 -> 1 -> 3 and 0 -> 2 -> 3.
Example 2
Input: graph = [[4,3,1],[3,2,4],[3],[4],[]]
Output: [[0,4],[0,3,4],[0,1,3,4],[0,1,2,3,4],[0,1,4]]
Constraints
n == graph.length2 <= n <= 150 <= graph[i][j] < ngraph[i][j] != i (i.e., there will be no self-loops).All the elements of graph[i] are unique.The input graph is guaranteed to be a DAG.
797. All Paths From Source to Target
Medium
30 Points
Backtracking
Depth-First Search
Breadth-First Search
Graph
Given a directed acyclic graph (DAG) of n nodes labeled from 0 to n - 1, find all possible paths from node 0 to node n - 1 and return them in any order.
The graph is given as follows: graph[i] is a list of all nodes you can visit from node i (i.e., there is a directed edge from node i to node graph[i][j]).
Examples
Example 1
Input: graph = [[1,2],[3],[3],[]]
Output: [[0,1,3],[0,2,3]]
Explanation: There are two paths: 0 -> 1 -> 3 and 0 -> 2 -> 3.
Example 2
Input: graph = [[4,3,1],[3,2,4],[3],[4],[]]
Output: [[0,4],[0,3,4],[0,1,3,4],[0,1,2,3,4],[0,1,4]]
Constraints
n == graph.length2 <= n <= 150 <= graph[i][j] < ngraph[i][j] != i (i.e., there will be no self-loops).All the elements of graph[i] are unique.The input graph is guaranteed to be a DAG.