By performing a DFS traversal and applying Tarjan's algorithm on each unvisited neighbor of a node, you can find all bridges in the graph.
Example Code in Python:
from collections import defaultdict
class Graph:
def __init__(self):
self.graph = defaultdict(list)
self.time = 0
def add_edge(self, u, v):
self.graph[u].append(v)
self.graph[v].append(u)
def bridge_util(self, u, visited, parent, low, disc):
visited[u] = True
disc[u] = self.time
low[u] = self.time
self.time += 1
for v in self.graph[u]:
if not visited[v]:
parent[v] = u
self.bridge_util(v, visited, parent, low, disc)
low[u] = min(low[u], low[v])
if low[v] > disc[u]:
print("Bridge found:", u, "-->", v)
elif v != parent[u]:
low[u] = min(low[u], disc[v])
def find_bridges(self):
V = len(self.graph)
visited = [False] * V
disc = [float("inf")] * V
low = [float("inf")] * V
parent = [-1] * V
for i in range(V):
if not visited[i]:
self.bridge_util(i, visited, parent, low, disc)
# Example usage:
g = Graph()
g.add_edge(0, 1)
g.add_edge(1, 2)
g.add_edge(2, 0)
g.add_edge(1, 3)
g.add_edge(3, 4)
g.find_bridges()
This Python code demonstrates how to find bridges in a graph using Tarjan's algorithm. The Graph class represents an undirected graph, and the find_bridges method identifies and prints the bridges in the graph.
