From 0 to 1 Data Structures & Algorithms in Java - Implementation Of Topological Sort

The video tutorial explains how to perform a topological sort on a graph, including detecting cycles. It covers the implementation of indegree calculation using both adjacency lists and matrices. The tutorial then walks through the topological sort algorithm, detailing how to set up an indegree map, identify vertices with zero indegree, and iteratively build the sorted list. The process also includes cycle detection by checking if all vertices are covered in the sort.

What is the primary purpose of performing a topological sort on a graph?

• To calculate the maximum flow

• To detect cycles in the graph

• To find the shortest path

• To sort vertices in a linear order

In the context of an adjacency list, what is the first step in calculating the indegree of a vertex?

• Verify the vertex is valid

• Count the number of edges

• Check if the vertex is connected to others

• Initialize the indegree to zero

How is the indegree of a vertex determined using an adjacency matrix?

• By counting the number of vertices

• By checking the appropriate row and column

• By summing the row values

• By checking the diagonal elements

What data structure is used to store vertices with zero indegree in the topological sort algorithm?

• Tree

• Stack

• Array

• Queue

During the topological sort, what happens to the indegree of adjacent vertices when a vertex is added to the sorted list?

• It remains unchanged

• It is incremented by one

• It is set to zero

• It is decremented by one

What indicates the presence of a cycle in the graph during the topological sort process?

• All vertices have non-zero indegree

• The sorted list is shorter than the number of vertices

• The graph has more than one component

• The queue becomes empty

Why is it important to check if the sorted list covers all vertices in the graph?

• To confirm the graph is directed

• To verify the graph is acyclic

• To ensure the graph is connected

• To determine the graph's density