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Graph data structure tutorial 4. Graph Traversal

prodevelopertutorial August 18, 2019

In the previous chapter we learnt about tree traversal. In this chapter we shall learn about graph traversal.

 

Graph traversal can be done in 2 ways:

  1. DFS: Depth first search
  2. BFS: Breadth first search

 

  1. Depth First Search

 

As the name suggests, we take a node and follow deep in the node and then stop if we reach a dead end. Then we backtrack to the starting node and then check if there are other nodes that are left out.

 

Let us understand with the help of a graph below:

Graph data structure tutorial 4. Graph Traversal

 

Now, let’s select a starting node. Let it be “A”. You can select any starting node.

 

From “A” we ca either go to node “C” or node “B”. We shall go to node “C”. Mark that node as visited [in green].

 

Graph data structure tutorial 4. Graph Traversal

 

From “C” we can go to node “D”, Then from node “D” to node “E”.

 

Graph data structure tutorial 4. Graph Traversal

 

Now we have reached at the end. Hence we backtrack to the previous node and check if there are any other nodes that have not been visited. As only node that is unvisited is “B”, we backtrack till “A”.

 

Graph data structure tutorial 4. Graph Traversal

 

Now, from “A” we see that node “B” has not been visited . then visit it.

 

Graph data structure tutorial 4. Graph Traversal

 

Hence the final result will be

 

A               C               D               E                B

 

Consider another example:

Graph data structure tutorial 4. Graph Traversal

 

So initially we shall start with node “A”, then traverse to node “B” then to “C” then to “D”.

Graph data structure tutorial 4. Graph Traversal

 

Then backtrack to “C”, now “G” node is unvisited. Visit it.

Graph data structure tutorial 4. Graph Traversal

 

Now backtrack to node “G” to “C” to “B” to “A”. Then visit “F”.

Graph data structure tutorial 4. Graph Traversal

 

Now again backtrack to “A”, then visit “E”.

Graph data structure tutorial 4. Graph Traversal

 

The order of nodes visited are:

 

A, B, C, D, G, F, E

 

Points to remember about DFS.

 

  1. DFS is used to know if 2 nodes have a path between them.
  2. We can only backtrack with the path that we have already visited.
  3. If there is a node that cannot be reached, then we need to restart the graph traversal from that path.

 

For example:

 

Graph data structure tutorial 4. Graph Traversal

 

Here as we have started the traversal from Node “C, we cannot reach “A” and “B”. hence we restart the traversal from “A” then reach “B”.

 

Hence the traversal will be:

Graph data structure tutorial 4. Graph Traversal

 

The path will be:

 

C               D               E                A               B

 

  1. Stack Data structure is used to realize graph traversal using DFS.

 

Graph traversal using BFS:

 

In previous section we have looked at graph traversal using DFS. In this section we shall look at graph traversal using BFS.

 

In Breadth First Search traversal we go level by level. Consider the example below:

Graph data structure tutorial 4. Graph Traversal

 

Now if we consider level by level, we can traverse it as below:

Graph data structure tutorial 4. Graph Traversal

 

Hence the output will be

 

A               C               B               D               E

 

Points to remember for BFS.

 

  1. BFS is used to find the shortest path between 2 nodes
  2. BFS is realized using queue.

Further Reading:

AJ’s definitive guide for DS and Algorithms. Click here to study the complete list of algorithm and data structure tutorial. 85+ chapters to study from.

 

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