802. Find Eventual Safe States
There is a directed graph of n
nodes with each node labeled from 0
to n - 1
. The graph is represented by a 0-indexed 2D integer array graph where graph[i]
is an integer array of nodes adjacent to node i
, meaning there is an edge from node i
to each node in graph[i]
.
A node is a terminal node if there are no outgoing edges. A node is a safe node if every possible path starting from that node leads to a terminal node (or another safe node).
Return an array containing all the safe nodes of the graph. The answer should be sorted in ascending order.
Example 1:
Input: graph = [[1,2],[2,3],[5],[0],[5],[],[]]
Output: [2,4,5,6]
Explanation: The given graph is shown above.
Nodes 5 and 6 are terminal nodes as there are no outgoing edges from either of them.
Every path starting at nodes 2, 4, 5, and 6 all lead to either node 5 or 6.
Example 2:
Input: graph = [[1,2,3,4],[1,2],[3,4],[0,4],[]]
Output: [4]
Explanation:
Only node 4 is a terminal node, and every path starting at node 4 leads to node 4.
Constraints:
n
== graph.length
n
<= 104graph[i].length
<= n
graph[i][j]
<= n - 1graph[i]
is sorted in a strictly increasing order.
class Solution {
public:
vector<int> eventualSafeNodes(vector<vector<int>>& graph) {
int numNodes = graph.size();
vector<int> indegree(numNodes);
vector<vector<int>> adj(numNodes);
for (int nodeID = 0; nodeID < numNodes; nodeID ++) {
for (int next : graph[nodeID]) {
adj[next].push_back(nodeID);
indegree[nodeID] ++;
}
}
queue<int> frontier;
for (int nodeID = 0; nodeID < numNodes; nodeID ++) {
if (indegree[nodeID] == 0) {
frontier.push(nodeID);
}
}
vector<bool> safeNodes(numNodes);
while (not frontier.empty()) {
int u = frontier.front();
frontier.pop();
safeNodes[u] = true;
for (const auto& next : adj[u]) {
indegree[next] --;
if (indegree[next] == 0) {
frontier.push(next);
}
}
}
vector<int> ans;
for (int nodeID = 0; nodeID < numNodes; nodeID ++) {
if (safeNodes[nodeID]) {
ans.push_back(nodeID);
}
}
return ans;
}
};
Jerry Wu12 Jul, 2023
class Solution:
def eventualSafeNodes(self, graph: List[List[int]]) -> List[int]:
n = len(graph)
cache = {}
def dfs(node):
if node in cache:
return cache[node]
cache[node] = False
for child in graph[node]:
if not dfs(child):
return False
cache[node] = True
return True
ans = []
for i in range(n):
if dfs(i):
ans.append(i)
return ans
Yen-Chi ChenThu, Jul 13, 2023