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Step 1: Choose a vertex in the graph and make it the source vertex & mark it visited.
Step 2: Determine a vertex which is adjacent to the source vertex and begun a new search if it is not already visited.
Step 3: Repeat step 2 via a new source vertex. While all adjacent vertices are visited, return to earlier source vertex and continue search from there.
If n refer to the number of vertices in the graph & the graph is represented through an adjacency matrix, then the total time taken to carry out DFS is O(n2). If G is revel by an adjacency list and the number of edges of G are e, then the time taken to carry out DFS is O(e).
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if two relations R and S are joined, then the non matching tuples of both R and S are ignored in
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Best Case: If the list is sorted already then A[i] T (n) = c1n + c2 (n -1) + c3(n -1) + c4 (n -1) = O (n), which indicates that the time complexity is linear. Worst Case:
Data array A has data series from 1,000,000 to 1 with step size 1, which is in perfect decreasing order. Data array B has data series from 1 to 1,000,000, which is in random order.
Sort the following array of elements using quick sort: 3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5, 8.
Let a be a well-formed formula. Let c be the number of binary logical operators in a. (Recall that ?, ?, ?, and ? are the binary logical operators). Let s be the number of proposit
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Have you ever thought about the handling of our files in operating system? Why do we contain a hierarchical file system? How do files saved & deleted under hierarchical directories
Merge sort is also one of the 'divide & conquer' classes of algorithms. The fundamental idea in it is to split the list in a number of sublists, sort each of these sublists & merge
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