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(10') 6. For each of the following code blocks, write the best (tightest) big-o time complexity...
Which big-O expression best characterizes the worst case time complexity of the following code? public static int foo(int N) ( int count = 0; int i1; while (i <N) C for (int j = 1; j < N; j=j+2) { count++ i=i+2; return count; A. O(log log N) B. O(log N2) C. O(N log N) D. O(N2)
Question 1 (25 pts) Find the running time complexity for the following code fragments. Express your answers using either the Big-O or Big-Θ notations, and the tightest bound possible. Justify your answers. for(int count O , i -0; i < n* n; i++) for(int i0 ; j <i; j++) count++ for(int count O , i -0; i
Show your work Count the number of operations and the big-O time complexity in the worst-case and best-case for the following code int small for ( i n t i = 0 ; i < n ; i ++) { i f ( a [ i ] < a [ 0 ] ) { small = a [ i ] ; } } Show Work Calculate the Big-O time complexity for the following code and explain your answer by showing...
Using C++ please explain What is the Big-O time complexity of the following code: for (int i=0; i<N; i+=2) { ... constant time operations... Select one: o a. O(n^2) O b. O(log n) c. O(n) O d. 0(1) What is the Big-O time complexity of the following code: for(int i=1; i<N; i*=2) { ... constant time operations... Select one: O O a. O(n^2) b. 0(1) c. O(n) d. O(log n) O What is the Big-O time complexity of the following...
1(5 pts): For each code fragment below, give the complexity of the algorithm (O or Θ). Give the tightest possible upper bound as the input size variable increases. The input size variable in these questions is exclusively n. Complexity Code public static int recursiveFunction (int n)f f( n <= 0 ) return 0; return recursiveFunction (n - 1) 1; for(int i 0i <n; i+) j=0; for ( int j k=0; i; k < < j++) for (int j; m <...
find complexity Problem 1 Find out the computational complexity (Big-Oh notation) of the code snippet: Code 1: for (int i = n; i > 0; i /= 2) { for (int j = 1; j < n; j *= 2) { for (int k = 0; k < n; k += 2) { // constant number of operations here } } } Code 2: Hint: Lecture Note 5, Page 7-8 void f(int n) { if (n...
For each code write the time complexity. For each of the following pieces of code, write down the time complexity that the code will run in, choosing from O(1), O(log n), O(n), O(n log n), O(n^2): def something (n) for i in range (n) return n Big-O:_____ for i in range (n) for j in range (5) print (i*j) Big-O:______ for i in range (n) for j in range (n n/3, 9): print (i*j) Big-O:_____ for i in range (521313*2213*11);...
Analyze the following code fragments and write down the Big-O estimates of the following code fragments. Provide a concise explanation how you got your answer. c. for (int j = 0; j < n; j++) { for (int k = 0; k < n; k++) cout << (j + k) << endl; } d. while (n > 1) { k += n *3; n = n / 2; } e. int temp = n; for (int j...
Analyze the following code fragments and write down the Big-O estimates of the following code fragments. Provide a concise explanation how you got your answer. c. for (int j = 0; j < n; j++) { for (int k = 0; k < n; k++) cout << (j + k) << endl; } d. while (n > 1) { k += n *3; n = n / 2; } e. int temp = n; for (int j...
1). What is the complexity of the following code snippet? { for (int count2 = 0; count2<n; count2++) { /*some sequence of O(1) step*/ } } select one: a. O(N^2) b. O(Log N) c. O(1) d. O(N!) 2). What is the complexity of the following code snippet? for (int count = 0; count<n; count++) { printsum(count) } select one: a. We need to know the complexity of the printsum() function. b. O(Log N) c. O(1) d. O(N) e. O(N^2) 3)....