Data Structures and Algorithms The Complete Masterclass - Graph Traversal

The video tutorial introduces graph traversal, comparing it with tree traversal and highlighting key differences. It explains the structure of graphs, emphasizing the absence of a root node and the concept of vertices and adjacency. The tutorial covers different types of graphs, such as directed and undirected, and discusses edge values. It also stresses the importance of tracking visited nodes during traversal. The session concludes with a brief overview of the next lecture, which will focus on implementing graph traversal in code.

What is a key structural difference between graphs and trees?

• Trees can have weighted edges.

• Trees have multiple starting nodes.

• Graphs can have cycles.

• Graphs have a root node.

In graph traversal, what is the term used for nodes directly connected to a starting node?

• Child nodes

• Sibling nodes

• Adjacent vertices

• Root nodes

How are relationships between nodes stored in a graph?

• As parent-child pairs

• In a binary tree format

• In an adjacency list

• As left and right children

What is a characteristic of a directed graph?

• Nodes have a root.

• Edges have a specific direction.

• All nodes are connected.

• Edges have no direction.

What does a weighted edge in a graph represent?

• The root of the graph

• The number of nodes connected

• The cost or distance between nodes

• The direction of the edge

Why is it important to track visited nodes in graph traversal?

• To identify the root node

• To avoid revisiting nodes and creating confusion

• To ensure all nodes are visited twice

• To find the shortest path

What traversal method starts by visiting all adjacent nodes before moving deeper?

• Depth-first search

• Breadth-first search

• In-order traversal

• Post-order traversal