Breadth-First Search
3/27/2017 6:16 PM
Presentation for use with the textbook, Algorithm Design and
Applications, by M. T. Goodrich and R. Tamassia, Wiley, 2015
Breadth-First Search
Breadth-first search
(BFS) is a general
technique for traversing
a graph
A BFS traversal of a
graph G

Breadth-First Search

L0
L1
A

B
C
D

L2
E
F


© 2015 Goodrich and Tamassia
Breadth-First Search
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© 2015 Goodrich and Tamassia
BFS Algorithm

Visits all the vertices and
edges of G
Determines whether G is
connected
Computes the connected
components of G
Computes a spanning
forest of G
L0
L1
Breadth-First Search
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A
E
L0
L1
L1
B
F
L0
C
E
© 2015 Goodrich and Tamassia
D
L1
F
Breadth-First Search
C
E
D
L1
L0
L1
A
B
C
D
E
L0
C
L1
D
F
A
B
C
F
D
E
F
Breadth-First Search
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F
L0
C
E
D
L1
F
5
C
E
D
L1
B
L2
F
A
C
E
D
F
A
B
L2
L0
A
B
L2
A
B
L2
L0
A
B
L2
A
B
L2
D
2
Example (cont.)
L0
C
Breadth-First Search
© 2015 Goodrich and Tamassia
Example (cont.)
B

Find and report a path
with the minimum
number of edges
between two given
vertices
Find a simple cycle, if
there is one
A
E
L1

unexplored vertex
visited vertex
unexplored edge
discovery edge
cross edge
A
A
L0

BFS on a graph with n
vertices and m edges
takes O(n + m ) time
BFS can be further
extended to solve other
graph problems
Example
The algorithm uses “levels” Li and a mechanism for setting and getting
“labels” of vertices and edges.
© 2015 Goodrich and Tamassia

C
E
© 2015 Goodrich and Tamassia
D
F
Breadth-First Search
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Breadth-First Search
3/27/2017 6:16 PM
Properties
Analysis
Notation
A
Gs: connected component of s

Property 1
B
BFS(G, s) visits all the vertices and
edges of Gs
C
E


F

A


L1
B
C
L2
D
E
F
7



Recall that
S v deg(v) = 2m
© 2015 Goodrich and Tamassia
Breadth-First Search
Compute the connected components of G
Compute a spanning forest of G
Find a simple cycle in G, or report that G is a
forest
Given two vertices of G, find a path in G between
them with the minimum number of edges, or
report that no such path exists
Applications
Breadth-First Search
9
DFS
BFS


Spanning forest, connected
components, paths, cycles
Shortest paths

Biconnected components

L0
A
B
C
E
D
L1
F
© 2015 Goodrich and Tamassia
A
B
L2
DFS
© 2015 Goodrich and Tamassia
8
DFS vs. BFS
We can use the BFS traversal algorithm, for a
graph G, to solve the following problems in
O(n + m) time

once as UNEXPLORED
once as DISCOVERY or CROSS
Each vertex is inserted once into a sequence Li
Method incidentEdges is called once for each vertex
BFS runs in O(n + m) time provided the graph is
represented by the adjacency list structure

Breadth-First Search
Applications


once as UNEXPLORED
once as VISITED
Each edge is labeled twice

L0
The path of Ts from s to v has i
edges
Every path from s to v in Gs has at
least i edges
© 2015 Goodrich and Tamassia


The discovery edges labeled by
BFS(G, s) form a spanning tree Ts
of Gs
For each vertex v in Li
D
Setting/getting a vertex/edge label takes O(1) time
Each vertex is labeled twice

Property 2
Property 3

C
E
D
F
BFS
Breadth-First Search
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DFS vs. BFS (cont.)
Back edge (v,w)

Cross edge (v,w)
w is an ancestor of v in
the tree of discovery
edges

L0
A
B
w is in the same level as
v or in the next level
C
E
D
L1
F
© 2015 Goodrich and Tamassia
B
L2
DFS
A
C
E
D
F
BFS
Breadth-First Search
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2