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Write down the algorithm of quick sort. An algorithm for quick sort: void quicksort ( int a[ ], int lower, int upper ) { int i ; if ( upper > lower ) { i = split ( a, lower, upper ) ; quicksort ( a, lower, i - 1 ) ; quicksort ( a, i + 1, upper ) ; } } int split ( int a[ ], int lower, int upper ){ int i, p, q, t ;
p = lower + 1 ; q = upper ; i = a[lower] ; while ( q >= p ) { while ( a[p] < i ) p++ ; while ( a[q] > i ) q-- ; if ( q > p ) { t = a[p] ; a[p] = a[q] ; a[q] = t ; } } t = a[lower] ; a[lower] = a[q] ; a[q] = t ; return q ; }
for (i = 0; i sequence of statements } Here, the loop executes n times. Thus, the sequence of statements also executes n times. Since we suppose the time complexity of th
The number of different directed trees with 3 nodes are ?? The number of disimilar directed trees with three nodes are 3
How sparse matrix stored in the memory of a computer?
Q. Write down a programme in C to create a single linked list also write the functions to do the following operations (i) To insert a new node at the end (ii
We have discussed already about three tree traversal methods in the earlier section on general tree. The similar three different ways to do the traversal -inorder , preorder, and p
Linked list representations contain great advantages of flexibility on the contiguous representation of data structures. However, they contain few disadvantages also. Data structur
Problem Your LC code is stored in a memory location as shown and the variable name is LC LC Memory address Content(LC code)
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
Create main method or a test class that creates 2 Element objects that are neighbours of each other, the first element temperature set at 100, the 2nd at 0 and use an appropriate h
In this respect depth-first search (DFS) is the exact reverse process: whenever it sends a new node, it immediately continues to extend from it. It sends back to previously explore
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