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Algorithm for determining strongly connected components of a Graph:
Strongly Connected Components (G)
where d[u] = discovery time of the vertex u throughout DFS , f[u] = finishing time of a vertex u throughout DFS, GT = Transpose of the adjacency matrix
Step 1: Use DFS(G) to calculate f[u] ∀u∈V
Step 2: calculate GT
Step 3: Execute DFS in GT
Step 4: Output the vertices of each of tree within the depth-first forest of Step 3 as a separate strongly connected component.
Q. Write down the algorithm which does depth first search through an un-weighted connected graph. In an un-weighted graph, would breadth first search or depth first search or neith
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Breadth-first search starts at a given vertex h, which is at level 0. In the first stage, we go to all the vertices that are at the distance of one edge away. When we go there, we
Draw trace table and determine the output from the below flowchart using following data (NOTE: input of the word "end" stops program and outputs results of survey): Vehicle = c
Example of worse case of time
A graph is a mathematical structure giving of a set of vertexes (v1, v2, v3) and a group of edges (e1, e2, e3). An edge is a set of vertexes. The two vertexes are named the edge en
Q. Make a BST for the given sequence of numbers. 45,32,90,34,68,72,15,24,30,66,11,50,10 Traverse the BST formed in Pre- order, Inorder and Postorder.
Q. Write down the algorithm for binary search. Which are the conditions under which sequential search of a list is preferred over the binary search?
The simplest implementation of the Dijkstra's algorithm stores vertices of set Q into an ordinary linked list or array, and operation Extract-Min(Q) is just a linear search through
application of threaded binary treee
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