Consider the following adjacency-lists representation of a DAG with 8 vertices and 13 edges: A: B: CEAF C: G F D: G C E: AF F: G: F H: DG Here is a graphical representation of the same DAG: -(B). ->(C)<---- --(D) (A)<------ (E) >(F)<------ (G)<- -(H) Give the topological order of the vertices that results from the DFS-based topological sort algorithm. As usual, perform the first DFS from vertex A. Answer Your answer should be a sequence of 8 uppercase letters, separated by whitespace.

Consider the following adjacency-lists representation of a DAG with 8 vertices and 13 edges: A: B: CEAF C: G F D: G C E: AF F: G: F H: DG Here is a graphical representation of the same DAG: -(B). ->(C)<---- --(D) (A)<------ (E) >(F)<------ (G)<- -(H) Give the topological order of the vertices that results from the DFS-based topological sort algorithm. As usual, perform the first DFS from vertex A. Answer Your answer should be a sequence of 8 uppercase letters, separated by whitespace.

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Throughout, a graph is given as input as an adjacency list. That is, G is a dictionary where the keysare vertices, and for a vertex v,G[v] = [u such that there is an edge going from v to u].In the case that G is undirected, for every edge u − v, v is in G[u] and u is in G[v] Question : Write the full pseudocode for BFS.Input: An undirected connected graph G, and a vertex v.Output: Visit every node of the graph using BFS, and output distance of every vertex from v.
In this task you will work with an undirected Graph G = {V, E}, where V = {f,p,s,b,l,j,t,c,d} and E = {(1,2), (1,3), (3,8), (4,8), (8,9), (1,7), (2,6), (2,3), (5,6), (6,7), (7,9), (8,1)}. Assume that the nodes are stored in an indexed linear structure (e.g., an array or a vector) numbered consecutively from 1 (node f) to 9 (node d). Run, by hand, a depth-first search (DFS) traversal of the graph G, starting at node p. When choosing which node to visit next amongst the possibilities, choose the one that is next in alphabetical order. Give your answer by listing the edges in the order that DFS will select.
In this task you will work with an undirected Graph G = {V, E}, where V = {f,p,s,b,l,j,t,c,d} and E = {(1,2), (1,3), (3,8), (4,8), (8,9), (1,7), (2,6), (2,3), (5,6), (6,7), (7,9), (8,1)}. Assume that the nodes are stored in an indexed linear structure (e.g., an array or a vector) numbered consecutively from 1 (node f) to 9 (node d). 1. Type up a tgf representation of the graph 2. Find a path from node l to node b with length 8, that passes through every vertex of the graph. List the nodes of that path. 3. The graph G contains cycles. What is the smallest number of vertices to remove in order to break all cycles?
How many undirected graphs (not necessarily connected) can be constructed out of a given set V= {V 1, V 2,…V n} of n vertices ? Group of answer choices 2^(n(n-1)/2) 2^n n(n-l)/2 n! Which of the following is an advantage of adjacency list representation over adjacency matrix representation of a graph? Adding a vertex in adjacency list representation is easier than adjacency matrix representation. In adjacency list representation, space is saved for sparse graphs. DFS and BSF can be done in O(V + E) time for adjacency list representation. These operations take O(V^2) time in adjacency matrix representation. Here is V and E are number of vertices and edges respectively. All of the above Given the starting vertex A, what is the visit order of the graph shown in Fig. 1 under the DFS traversal algorithm. ABDCFE ACBDFE ABCDFE ADBCEF Assume you have the adjacency matrix representing a graph. 1 represents a connection while -1 represents a lack of one:[-1, 1, - 1][-1, -1, 1][1, -1,…
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given an ordering of vertices in a graph, implement a minimum coloring of the vertices in C language. (using adjacency list not matrix)he output would be Vertex 1->2 Color->Red, Vertex 2->3 Color ->Blue with an input of The input would be a string of vertex like 2358691.
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Draw a tree with 14 vertices Draw a directed acyclic graph with 6 vertices and 14 edges Suppose that your computer only has enough memory to store 40000 entries. Which best graph data structure(s) – you can choose more than 1 -- should you use to store a simple undirected graph with 200 vertices, 19900 edges, and the existence of edge(u,v) is frequently asked? - Adjacency Matrix - Adjacency List - Edge List
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''In graph theory, a component, sometimes called a connected component,of an undirected graph is a subgraph in which anytwo vertices are connected to each other by paths.Example: 1 3------------7 | | 2--------4 | | | | output = 2 6--------5''' # Code is Here def dfs(source,visited,adjacency_list): ''' Function that performs DFS ''' visited[source] = True for child in adjacency_list[source]: if not visited[child]: dfs(child,visited,adjacency_list) def count_components(adjacency_list,size): ''' Function that counts the Connected components on bases of DFS. return type : int ''' count = 0 visited = [False]*(size+1) for i in range(1,size+1): if not visited[i]: dfs(i,visited,adjacency_list) count+=1 return count def main(): """ Example application """ node_count,edge_count = map(int, input("Enter the Number of Nodes and Edges…
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