What is the big o cost of this method? int count = 0; int i = 1; while(i < n){ for (j = 1; j < n*n; j *= n) { count++; } i *= 2; } System.out.println(count);
Number of values for i = log(n) Number of values for j = logn(n^2) = 2 So, Time complexity = O(log(n)*2) = O(log(n))
O(log(n))
#9 What is time complexity of fun()? int fun(int n) { int count = 0; for (int i = n; i > 0; i /= 2) for (int j = 0; j < i; j++) count += 1; return count; } Group of answer choices O(n^2) O(nLogn) O(n) O(nLognLogn)
Find Big-O notation for the following algorithm: int function9(int n) { int ij for (i-0; in; i++) for (0; j<n; j++ if (j1) break return j; } int function9(int n) { int ij for (i-0; in; i++) for (0; j
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...
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)
(10') 6. For each of the following code blocks, write the best (tightest) big-o time complexity i) for (int i = 0; ǐ < n/2; i++) for (int j -0: ni j++) count++ i) for (int í = 0; i < n; i++) for (int ni j0 - for (int k j k ni kt+) count++ İİİ) for (int í ー 0; i < n; i++) for(int j = n; j > 0; j--) for (int k = 0; k...
JAVA: What is the Big-O cost of the following code (n is a large positive integer)? int count = 0; for (int i = 1; i < n; i *= 2) { for (int k = i; k <= i + 8; k ++ ) { count ++; } }
1. Determine the appropriate big-o expression for each of the following functions, and put your answer in the table we have provided in section 2-1 of ps5_parti. We've included the answer for the first function. (Note: We're using the “ symbol to represent exponentiation.) a (n) = 5n + 1 b. b(n) = 5 - 10n - n^2 o c(n) = 4n + 2log (n) d. e. d(n) = 6nlog (n) + n^2 e(n) = 2n^2 + 3n^3 - 7n...
Determine the Big 0 provide the order (Big O) of the execution speed also determine the exact execution speed. public class CountIt { public long SnippetNestedLoop(long n) { long i, j, x = 0; i=0; x++; while(i<n){ x++; //i<n // SomeStatement // j = 0; // j < n // SomeStatement // j++; // Can you explain why is this here? // i++; // Can you explain why is this here? Ans: i < n } } } x++; return...
What is the runtime of each method? Give answer in Θ(big Theta) notation as a function of n, give a brief explanation. A. public static int method1(int n){ int mid = n/2; for (int i = mid; i >= 0; i--) System.out.println(i); for (int i = mid + 1; i <= n; i++) System.out.println(i); return mid; } B. public static int method2(int n){ for (int i = n; i >= 0; i / 3){ System.out.println(i ); } return mid; }...
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...