Database System Concepts
7th Edition
ISBN: 9780078022159
Author: Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher: McGraw-Hill Education
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- def sorting(x, i, j) if j+1-i < 10 then Mergesort(x, i, j); t1 = i + (j+1-i)/3 t2 = i + 2*(j+1-i)/3 Sorting(x, i, t2) Sorting(x, i, j) Sorting(x, i, t2) // x is an array, I and j are first and last indices of this part of the array // on k elements, takes O(k log k) time worst case analysis?arrow_forwarddef f(A, B): 8 + 1 if A <= 0: } return B else: return f(A-1, B) double f(int A, int B) { if (A <= 0) { return B; } else { return f(A-1, B); What is the time complexity of the function ()? Select one: OA 0(2^A) OB. O(A^2) OC. O(A log 2 A) OD. None of the others OE O(A)arrow_forwardExample function void f() { int array[10]; read(array, 10); reverse(array, 10); print(array, 10); } Stack Frame saved $ra = 4 bytes int array[10] (40 bytes) Figure 7.6: Example of a function f and its corresponding stack frame 5. Suppose we rewrite function f (Figures 7.6) to have an integer parameter n. The local array is now declared to have n integers (rather than 10). This means that the size of the stack frame size of function f will depend on n. Rewrite the function f in MIPS assembly language. Hint: you may use the $fp register (in addition to $sp) to implement the function f. void f(int n) { int array[n]; read(array, n); reverse(array, n); print(array, n); }arrow_forward
- 2. What will be the time complexity of the given code in terms of n in Big-O notation. vectorvisited(n,false); for(int i=0;iarrow_forward1. Consider the following dynamic programming implementation of the Knapsack problem: #include int find_max(int a, int b) { if(a > b) return a; return b; } int knapsack(int W, int *wt, int *val,int n) { int ans[n + 1][W + 1]; int itm,w; for(itm = 0; itm <= n; itm++) ans[itm][0] = 0; for(w = 0;w <= W; w++) ans[0][w] = 0; for(itm = 1; itm <= n; itm++) { for(w = 1; w <= W; w++) { if(wt[itm - 1] <= w) ans[itm][w] = ______________; else ans[itm][w] = ans[itm - 1][w]; } } return ans[n][W]; } int main() { int w[] = {10,20,30}, v[] = {60, 100, 120}, W = 50; int ans = knapsack(W, w, v, 3); printf("%d",ans); return 0; } Which of the following lines completes the above code? A. find_max(ans[itm – 1][w – wt[itm – 1]] + val[itm – 1], ans[itm – 1][w]) B. find_max(ans[itm – 1][w –…arrow_forward2. a) Show the status of a QUEUE and a Priority QUEUE (Data in Descending Order) for the following operations, where both QUEUES are implemented by an array of size, m=3. Here, Enqueue and Dequeue mean insert and delete respectively, and x=last two digits of your student id+2, y=x+3, z=x+y and p=y+z. last two digits student id Enqueue(z), Enqueue(p), Dequeue(), Enqueue(y), Dequeue() b) Draw a complete binary tree and then build the min-heap tree from the following data, where x= last two digits of your student id+100, y=x+30, and z=x+y. Finally, sort the data in descending order using the heapsort algorithm. last two digits student id = 85 10 x 20 8 y z c) Two disjoint sets {y, p, z, x} and {r, t} are given, where maximum one of a set is the representative of that set. Determine UNION(Find(x), Find(t)). How can you check x and y are in the same set using Find operation? Here, x=last two digits of your student id+2, y=x+3, Z=x+y, p=y+z, r=x+2, t=900. last two digits student id = 85arrow_forwardarrow_back_iosarrow_forward_ios
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