Table of Contents
- 1 What is the time complexity of DFS if the adjacency list is used?
- 2 What is the time complexity of DFS justify your answer with an example?
- 3 Which of the following is an advantage of adjacency list representation over adjacency?
- 4 How do you calculate the complexity of DFS?
- 5 What is adjacency matrix in depth first search (DFS)?
What is the time complexity of DFS if the adjacency list is used?
The Time complexity of DFS is also O(V + E) when Adjacency List is used and O(V^2) when Adjacency Matrix is used, where V stands for vertices and E stands for edges. 6.
What is the time complexity of following operation in adjacency list and adjacency matrix?
Time/Space complexity of adjacency matrix and adjacency list. I am reading “Algorithms Design” By Eva Tardos and in chapter 3 it is mentioned that adjacency matrix has the complexity of O(n^2) while adjacency list has O(m+n) where m is the total number of edges and n is the total number of nodes.
What is the time complexity of DFS justify your answer with an example?
The time complexity of DFS if the entire tree is traversed is O ( V ) O(V) O(V) where V is the number of nodes. In the case of a graph, the time complexity is O ( V + E ) O(V + E) O(V+E) where V is the number of vertexes and E is the number of edges.
What is the space complexity of standard DFS?
For DFS, which goes along a single ‘branch’ all the way down and uses a stack implementation, the height of the tree matters. The space complexity for DFS is O(h) where h is the maximum height of the tree.
Which of the following is an advantage of adjacency list representation over adjacency?
Which of the following is an advantage of adjacency list representation over adjacency matrix representation of a graph? In adjacency list representation, space is saved for sparse graphs. Deleting a vertex in adjacency list representation is easier than adjacency matrix representation.
What is the time complexity of implementing DFS?
How do you calculate the complexity of DFS?
So, the complexity of DFS is O(V * V) = O(V^2). If your graph is implemented using adjacency lists, wherein each node maintains a list of all its adjacent edges, then, for each node, you could discover all its neighbors by traversing its adjacency list just once in linear time.
What is the time complexity of BFS algorithm?
44 The basic algorithm for BFS: set start vertex to visited load it into queue while queue not empty for each edge incident to vertex if its not visited load into queue mark vertex So I would think the time complexity would be: v1 + (incident edges) + v2 + (incident edges) + …. + vn + (incident edges)
What is adjacency matrix in depth first search (DFS)?
Depth First Search (DFS) has been discussed in this article which uses adjacency list for the graph representation. In this article, adjacency matrix will be used to represent the graph.
What is the complexity of an adjacency list of vertices?
2 If in an adjacency list, each vertex is connected to all other vertices the would the complexity be equivalent to O(V+E)=O(V+V^2)=O(V^2). E=V^2 because the most number of edges = V^2. – Max Feb 24 ’17 at 8:29