Given the graph G from Question 2, using the Graph Depth-First Search with a Stack algorithm, please do the following: I Assume that the start node is 0 (e.g. node = 0). Demonstrate a step-by-step, manual desk-check execution of the DFS algorithm, showing the values of all variables and arrays (e.g. visited, S) for each step in each cycle of each loop, as demonstrated in class. [ Algorithm: Graph depth-first search with a stack. StackDFS (G, node) → visited Input: G = (V, E), a graph node, the starting vertex in G Output: visited, an array of size |V| such that visited[i] is TRUE if we have visited node i, FALSE otherwise

Given the graph G from Question 2, using the Graph Depth-First Search with a Stack algorithm, please do the following: I Assume that the start node is 0 (e.g. node = 0). Demonstrate a step-by-step, manual desk-check execution of the DFS algorithm, showing the values of all variables and arrays (e.g. visited, S) for each step in each cycle of each loop, as demonstrated in class. [ Algorithm: Graph depth-first search with a stack. StackDFS (G, node) → visited Input: G = (V, E), a graph node, the starting vertex in G Output: visited, an array of size |V| such that visited[i] is TRUE if we have visited node i, FALSE otherwise

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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1. Input: An undirected weighted graph G = (V, E, w)2. Output: An MST T = (V, E) of G3. T ← Ø4. Sort edges of G in non-increasing order and place them in a queue Q.5. repeat6. Remove the first edge (u, v) from Q and add it to T if it does not form a cyclewith the edges edge that are already included in T .7. until there are n − 1 edges in T .We can use union-find data structure to find whether the two endpoints of theselected edge are in the same set (the current MST fragment). It can be shown thatthis algorithm is correct and has a time complexity of O(m log n) [1].Give Python Implementation of algo
True or false help
In the following G, each adjacency list is sorted in increasing alphabetical order. B H Draw the component graph GSCC of G.
1 6 0 2 4 7 3 5 Graph G
Consider the following graph. Start from vertex x, use the Depth First Search (DFS) algorithm (described in the textbook) to compute the DFS tree(s). Show intermediate results similar to the textbook example and show the final DFS tree(s). It is assumed that in the adjacency list representation, all vertices are stored according to their alphabetical order. In other words, a vertex’s neighbors should be explored by their relative alphabetical order.
4. Consider the graph G, shown below, which is simply a copy of K5. 02 V3 5 V1 24 V5 How many distinct spanning trees does G have? (Hint: Break up your search by the isomorphism type of the tree, as discovered on the previous page. So for example, start by counting the paths of length 5 in G. Then proceed to the next type of tree with 5 vertices. The total number of trees is 125, but please use this answer only to check that your solution is complete!)
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Given two (singly) linked lists, determine if the two lists intersect. Return the intersecting node. Note that the intersection is defined based on reference, not value. That is, if the kthnode of the first linked list is the exact same node (by reference) as the jth node of the secondlinked list, then they are intersecting.