802 Find Eventual Safe States
1. Question
In a directed graph, we start at some node and every turn, walk along a directed edge of the graph. If we reach a node that is terminal (that is, it has no outgoing directed edges), we stop.
Now, say our starting node is_eventually safe _if and only if we must eventually walk to a terminal node. More specifically, there exists a natural numberKso that for any choice of where to walk, we must have stopped at a terminal node in less thanKsteps.
Which nodes are eventually safe? Return them as an array in sorted order.
The directed graph hasNnodes with labels0, 1, ..., N-1, whereNis the length ofgraph. The graph is given in the following form:graph[i]is a list of labelsjsuch that(i, j)is a directed edge of the graph.
Example:
Input: graph = [[1,2],[2,3],[5],[0],[5],[],[]]
Output:
[2,4,5,6]
Here is a diagram of the above graph.
Note:
graphwill have length at most10000.The number of edges in the graph will not exceed
32000.Each
graph[i]will be a sorted list of different integers, chosen within the range
[0, graph.length - 1].
2. Implementation
(1) BFS Topological Sort
class Solution {
public List<Integer> eventualSafeNodes(int[][] graph) {
// Method 1: BFS topologicl sort
List<Integer> res = new ArrayList<>();
if (graph == null || graph.length == 0) {
return res;
}
int n = graph.length;
int[] outDegree = new int[n];
List<Set<Integer>> adjList = new ArrayList<>();
for (int i = 0; i < n; i++) {
adjList.add(new HashSet<>());
}
for (int i = 0; i < n; i++) {
for (int neighbor : graph[i]) {
adjList.get(neighbor).add(i);
++outDegree[i];
}
}
Queue<Integer> queue = new LinkedList<>();
for (int i = 0; i < n; i++) {
if (outDegree[i] == 0) {
queue.add(i);
}
}
while (!queue.isEmpty()) {
int curNode = queue.remove();
res.add(curNode);
for (int nextNode : adjList.get(curNode)) {
if (--outDegree[nextNode] == 0) {
queue.add(nextNode);
}
}
}
Collections.sort(res);
return res;
}
}3. Time & Space Complexity
BFS Topological Sort:
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