Describe the worst case running time of the following pseudocode functions in Big-Oh notation in terms...
4. Big-Oh and Rune time Analysis: describe the worst case running time of the following pseudocode functions in Big-Oh notation in terms of the variable n. howing your work is not required (although showing work may allow some partial t in the case your answer is wrong-don't spend a lot of time showing your work.). You MUST choose your answer from the following (not given in any particular order), each of which could be re-used (could be the answer for...
Give a big-Oh characterization, in terms of n,of the running time for each of the following code segments (use the drop-down): - public void func1(int n) { A. @(1). for (int i = n; i > 0; i--) { System.out.println(i); B. follogn). for (int j = 0; j <i; j++) System.out.println(j); c.e(n). System.out.println("Goodbye!"); D.@(nlogn). E.e(n). F.ein). public void func2 (int n) { for (int m=1; m <= n; m++) { system.out.println (m); i = n; while (i >0){ system.out.println(i); i...
6. Using big-oh notation, give the runtime for each of the following recursive functions. You do not need to justify your answers: a) Int nonesense (int n) if (n <0) return 1; return nonsense (n-2) 1; b) int no nonesense (int n) if (n <0) return 1; return no_nonsense (n-1)+ no nonsense (n-1)
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)
Describe the order of magnitude of the following code section using Big(O) notation. k=0; for (i= 0; i<N; i++)
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...
Provide a "big oh" run-time analysis for each of the following. When a value of “n” is used, it is the size of the input. 4.) void problem 40 cin n min max for (int i min i n, i++) for (int j- 1: j< max, j++) tota while (total n tota total 2 total 5.) void problem 50 cin n; for (int i 0: i n, i++) for (int j 0; j i2; j++) for (int k 0; k...
Compute the Big O notation. Explain how you got the answer. on W NA 1 public String modify (String str) { if (str.length() <= 1) return ""; int half = str.length() / 2; modify(str.substring(half)); 5} 1 2 3 for (int i = 0; i<n; i++) { for (int j 0; j < 5; j++) { for (int k = 0; k<n; k++) { 4 if ((i != j) && (i != k)) { 5 System.out.println(k); 6 } 7 } 8...
Problem 1. Select the running time of each function. void print_array (int* A, int n) for (int í 0; i < n; ++i) cout << A[i] << endl; void print_array pairs (int* A, int n) for (inti 0; i < n; ++i) for (int j 0; j < n; ++j) cout << Ai] ALj]< endl; void print_array_start(int* A, int n) for (int i 0; i < 100 ; ++i) cout << A[i] << endl; void print_array_alt (int* A, int n)...
Please provide the big oh notation for running time and space complexity for the following functions (available, into, out, size, and printAll): int SplayTreeInventory::available(string id){ Node* temp=stmap->findSplay(id); if(temp!=NULL) return temp->value; else return -1; } void SplayTreeInventory::into(string id, int amount) { Node* temp=stmap->findSplay(id); if(temp==NULL){ stmap->putSplay(id, amount); } else{ temp->key+=amount; } } void SplayTreeInventory::out(string id, int amount) { Node* temp=stmap->findSplay(id); if(temp==NULL){ } else{ if(temp->value<=amount) stmap->erase(id); else temp->value-=amount; } } int SplayTreeInventory::size() { return stmap->size(); } void SplayTreeInventory::printAll() { printAllHelper(this->stmap->root); }