Cycle detection in directed graph - cocoder39/coco39_LC GitHub Wiki
Reference: https://www.geeksforgeeks.org/detect-cycle-in-a-graph/
Option 1: DFS
Snap interview problem: this solution can be used to solve a variant of LC Course Schedule problem. Eg, given prerequisites, and a target course, find the ordering to get the course and detect loop if there exists loop.
tradeoffs between topological sort vs dfs: topological sort is good at inferring the ordering for all courses while dfs is efficient to infer the ordering for a specific course
subproblem 1 - get ordering: which can be solved by regular DFS with a visited set subproblem 2 - loop detection: check if next node to be visited is already in recursion path (indicating a loop is formed)
visited set is superset of recursion path. all nodes in recursion path should be in visited set but visited set could contain nodes in other recursion paths
# Python program to detect cycle
# in a graph
from collections import defaultdict
class Graph():
def __init__(self,vertices):
self.graph = defaultdict(list)
self.V = vertices
def addEdge(self,u,v):
self.graph[u].append(v)
def isCyclicUtil(self, v, visited, recStack):
# Mark current node as visited and
# adds to recursion stack
visited[v] = True
recStack[v] = True
# Recur for all neighbours
# if any neighbour is visited and in
# recStack then graph is cyclic
for neighbour in self.graph[v]:
if visited[neighbour] == False:
if self.isCyclicUtil(neighbour, visited, recStack) == True:
return True
elif recStack[neighbour] == True:
return True
# The node needs to be popped from
# recursion stack before function ends
recStack[v] = False
return False
# Returns true if graph is cyclic else false
def isCyclic(self):
visited = [False] * (self.V + 1)
recStack = [False] * (self.V + 1)
for node in range(self.V):
if visited[node] == False:
if self.isCyclicUtil(node,visited,recStack) == True:
return True
return False
g = Graph(4)
g.addEdge(0, 1)
g.addEdge(0, 2)
g.addEdge(1, 2)
g.addEdge(2, 0)
g.addEdge(2, 3)
g.addEdge(3, 3)
if g.isCyclic() == 1:
print "Graph contains cycle"
else:
print "Graph doesn't contain cycle"
# Thanks to Divyanshu Mehta for contributing this code
Option 2: topological sort
check in-degree
Option 3: BFS
EG given a directed graph and a target node, find shorted cycle that includes target (Google interview)
bfs traversal + assign a rank to each layer -> once rank collision -> cycle