The pseudocode algorithm provided calculates the total number of articulation points in a graph.
Example
# Here, we are writing down the algorithm to demonstrate the concept of
# Articulation Points and Bridges with their edge cases, functions, and algorithmic
# loops included articulating the brute force approach
function find_articulation_points(adj[][], V)
count = 0
for i = 0 to V
visited[i] = false
initial_val = 0
for i = 0 to V
if visited[i] == false
DFS(adj, V, visited, i)
initial_val = initial_val+1
# the below for loop code snippet help us with looping over the entire graph
for i=0 to V
for j = 0 to V
visited[j] = false
copy[j] = adj[i][j]
adj[i][j]=adj[j][i]=0
# for loop code snippet helping us with mapping the visited nodes in a graph
nval = 0
for j= 0 to V
if visited[j] == false AND j != i
nval = nval + 1
DFS(adj, n, visited, j)
# edge case shielding for the visited nodes in a graph data structure algorithm
if nval > initial_val
count = count + 1
for j= 0 to V
adj[i][j] = adj[j][i] = copy[j]
# after the traversal, it returns us the number of articulation points
# of the given graph structure
return count
# end of the Pseudocode algorithm of articulation points
# in a graph data structure
Pseudo Code
Example
# Here, we are writing down the algorithm to demonstrate the concept of
# Articulation Points and Bridges with their edge cases, functions, and algorithmic
# loops included articulating the brute force approach
time = 0
function DFS(adj[][], disc[], low[], visited[], parent[], AP[], vertex, V)
visited[vertex] = true
disc[vertex] = low[vertex] = time+1
child = 0
# the below for loop code snippet help us with looping over the entire graph
for i = 0 to V
if adj[vertex][i] == true
if visited[i] == false
child = child + 1
# for loop code snippet helping us with mapping the visited nodes in a graph
parent[i] = vertex
DFS(adj, disc, low, visited, parent, AP, i, n, time+1)
low[vertex] = minimum(low[vertex], low[i])
if parent[vertex] == nil and child > 1
AP[vertex] = true
if parent[vertex] != nil and low[i] >= disc[vertex]
AP[vertex] = true
# edge case shielding for the visited nodes in a graph data structure algorithm
else if parent[vertex] != i
low[vertex] = minimum(low[vertex], disc[i])
# after the traversal, it returns us the number of articulation points
# of the given graph structure
# end of the Pseudocode algorithm of articulation points
# in a graph data structure
Bridges
The link between two vertices, such as x and y, within a graph is known as an articulation point. Once this link is eliminated, there are no remaining traversal routes. This action can expose weaknesses in the network accessible to the device or system. Similar to an articulation point, a thorough examination of every vertex in the complete graph data structure is required through brute force to verify the existence of paths by removing connections and confirming vertex connectivity.
Pseudo Code
Example
# Here, we are writing down the algorithm to demonstrate the concept of
# Articulation Points and Bridges with their edge cases, functions, and algorithmic
# loops included articulating the brute force approach
function find_bridges(adj[][], V, Edge[], E, isBridge[])
for i = 0 to E
adj[Edge[i].u][Edge[i].v]=adj[Edge[i].v][Edge[i].u]=0
for j = 0 to V
visited[j] = false
Queue.Insert(Edge[i].u])
visited[Edge[i].u] = true
check = false
while Queue.isEmpty() == false
x = Queue.top()
if x == Edge[i].v
check = true
BREAK
Queue.Delete()
# the below for loop code snippet help us with looping over the entire graph
for j = 0 to V
if adj[x][j] == true AND visited[j] == false
Queue.insert(j)
visited[j] = true
adj[Edge[i].u][Edge[i].v]=adj[Edge[i].v][Edge[i].u]=1
if check == false
isBridge[i] = true
# end of the Pseudocode algorithm of articulation points, bridges
# in a graph data structure