DFS and BFS Difference | Gate Vidyalay

Depth First Search-

Depth First Search or DFS is a graph traversal algorithm.
It is used for traversing or searching a graph in a systematic fashion.
DFS uses a strategy that searches “deeper” in the graph whenever possible.
Stack data structure is used in the implementation of depth first search.

DFS Example-

Consider the following graph-

The depth first search traversal order of the above graph is-

A, B, E, F, C, D

Depth First Search Algorithm-

DFS (V,E)

for each vertex u in V[G]

do color[v] ← WHITE

π[v] ← NIL

time ← 0

for each vertex v in V[G]

do if color[v] ← WHITE

then Depth_First_Search(v)

Depth_First_Search (v)

color[v] ← GRAY

time ← time + 1

d[v] ← time

for each vertex u adjacent to v

do if color[u] ← WHITE

π[u] ← v

Depth_First_Search(u)

color[v] ← BLACK

time ← time + 1

f[v] ← time

Explanation-

The above depth first search algorithm is explained in the following steps-

Step-01

Create and maintain 4 variables for each vertex of the graph.

For any vertex ‘v’ of the graph, these 4 variables are-

1. color[v]-

This variable represents the color of the vertex ‘v’ at the given point of time.
The possible values of this variable are- WHITE, GREY and BLACK.
WHITE color of the vertex signifies that it has not been discovered yet.
GREY color of the vertex signifies that it has been discovered and it is being processed.
BLACK color of the vertex signifies that it has been completely processed.

2. Π[v]-

This variable represents the predecessor of vertex ‘v’.

3. d[v]-

This variable represents a timestamp when a vertex ‘v’ is discovered.

3. f[v]-

This variable represents a timestamp when the processing of vertex ‘v’ is completed.

Step-02

For each vertex of the graph, initialize the variables as-

color[v] = WHITE
π[v] = NIL
time = 0 (Global Variable acting as a timer)

Step-03

Repeat the following procedure until all the vertices of the graph become BLACK-

Consider any white vertex ‘v’ and call the following Depth_First_Search function on it.

Depth_First_Search (G,v)

1. color[v] = GRAY

2. time = time + 1

3. d[v] = time

4. For each adjacent WHITE vertex ‘u’ of ‘v’, set π[u] = v and call Depth_First_Search (G,u)

5. color[v] = BLACK

6. time = time + 1

7. f[v] = time

DFS Time Complexity-

The total running time for Depth First Search is θ (V+E).

Types of Edges in DFS-

After a DFS traversal of any graph G, all its edges can be put in one of the following 4 classes-

Tree Edge
Back Edge
Forward Edge
Cross Edge

1. Tree Edge-

A tree edge is an edge that is included in the DFS tree.

2. Back Edge-

An edge from a vertex ‘u’ to one of its ancestors ‘v’ is called as a back edge.

A self-loop is considered as a back edge.

A back edge is discovered when-

DFS tries to extend the visit from a vertex ‘u’ to vertex ‘v’
And vertex ‘v’ is found to be an ancestor of vertex ‘u’ and grey at that time.

3. Forward Edge-

An edge from a vertex ‘u’ to one of its descendants ‘v’ is called as a forward edge.

A forward edge is discovered when-

DFS tries to extend the visit from a vertex ‘u’ to a vertex ‘v’
And finds that color(v) = BLACK and d(v) > d(u).

4. Cross Edge-

An edge from a vertex ‘u’ to a vertex ‘v’ that is neither its ancestor nor its descendant is called as a cross edge.

A cross edge is discovered when-

DFS tries to extend the visit from a vertex ‘u’ to a vertex ‘v’
And finds that color(v) = BLACK and d(v) < d(u).

PRACTICE PROBLEM BASED ON DEPTH FIRST SEARCH-

Problem-

Compute the DFS tree for the graph given below-

Also, show the discovery and finishing time for each vertex and classify the edges.

Solution-

Initially for all the vertices of the graph, we set the variables as-

color[v] = WHITE
π[v] = NIL
time = 0 (Global)

Let us start processing the graph from vertex U.

Step-01:

color[U] = GREY
time = 0 + 1 = 1
d[U] = 1

Step-02:

π[V] = U
color[V] = GREY
time = 1 + 1 = 2
d[V] = 2

Step-03:

π[Y] = V
color[Y] = GREY
time = 2 + 1 = 3
d[Y] = 3

Step-04:

π[X] = Y
color[X] = GREY
time = 3 + 1 = 4
d[X] = 4

Step-05:

When DFS tries to extend the visit from vertex X to vertex V, it finds-

Vertex V is an ancestor of vertex X since it has already been discovered
Vertex V is GREY in color.

Thus, edge XV is a back edge.

Step-06:

color[X] = BLACK
time = 4 + 1 = 5
f[X] = 5

Step-07:

color[Y] = BLACK
time = 5 + 1 = 6
f[Y] = 6

Step-08:

color[V] = BLACK
time = 6 + 1 = 7
f[V] = 7

Step-09:

When DFS tries to extend the visit from vertex U to vertex X, it finds-

Vertex X has already been completely processed i.e. vertex X has finished and is black.
But vertex U has still not finished.

Alternatively,

When DFS tries to extend the visit from vertex U to vertex X, it finds-

Color(X) = BLACK
d(X) > d(U)

Thus, edge UX is a forward edge.

Step-10:

color[U] = BLACK
time = 7 + 1 = 8
f[U] = 8

Step-11:

color[W] = GREY
time = 8 + 1 = 9
d[W] = 9

Step-12:

When DFS tries to extend the visit from vertex W to vertex Y, it finds-

Vertex Y has already been completely processed i.e. vertex Y has finished.
Vertex Y is neither a descendant nor an ancestor of vertex W.