analysis of the running time complexity
C=k*z;
for(i=1;i<n;i++)
{
X=c-a;
}
for(j=0;j<n;j++)
{
C=C+d;
}
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discrete math (1) (15 pts) Time Complexity Analysis 1) (5 pts) What is the time complexity...
discrete math
(1) (15 pts) Time Complexity Analysis 1) (5 pts) What is the time complexity of the following code segment? Explain your answer; otherwise, you can't get full mark from this question. for(int i=1; i<n; i*=2) { sum-0; sum++; Answer: 2) (5 pts) What is the time complexity of the following code segment? Explain your answer; otherwise, you can't get full mark from this question. for(int j=0; j<n; j++){ for (int k=0; k<n; k++) { for (int =0; i<n;...
For each of the following six program fragments: a. Give an analysis of the running time...
For each of the following six program fragments: a. Give an analysis of the running time (Big-Oh will do). b. Implement the code in the language of your choice, and give the running time for several values of N. Pseudo Code Implementation Analysis of runtime time (Big-Oh) (1) sum = 0; for(i = 0; i < n; ++i) ++sum; (2) sum = 0; for(i = 0; i < n; ++i) for(j = 0; j<n; ++i) ++sum; (3) sum = 0;...
4. Big-Oh and Rune time Analysis: describe the worst case running time of the following pseudocode...
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...
II. ALGORITHM COMPLEXITY AND ASYMPTOTIC ANALYSIS The below visual representations of iterative looping structures are provided...
II. ALGORITHM COMPLEXITY AND ASYMPTOTIC ANALYSIS The below visual representations of iterative looping structures are provided for Question 3 through Question 20. Algorithm 1 Algorithm 2 log.n 256 Algorithm 3 Algorithm 4 n (10) Match one of our algorithms to the below code snippet. for (int i = 0; i <n; i++) { for(int j = 0; j<n; j++) { for (int k = 0; k<n; k++) { nop++; nop++; nop++; } } } for (int i = 0; i...
Compute the time complexity for each of the following two program fragments with respect to N....
Compute the time complexity for each of the following two program fragments with respect to N. Show your steps in reaching your answer. 1) for(i=1; i < N; i = i*2) { for(j=0;j // Operations with constant time… } } 2) for(i = 0; i < sqrt(N); i++){ for(j=1; j < i+8; j++){ for(k=0;k // Operations with constant time… } } }
Using C++ please explain What is the Big-O time complexity of the following code: for (int...
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...
Exercises • Determine running time for the following code fragments: (a) a = b + c;...
Exercises • Determine running time for the following code fragments: (a) a = b + c; d = a + e; (b) sum = 0; for (i=0; i<3; i++) for (j=0; j<n; j++) sum++; (c) sum=0; for (i=0; i<n<n; i++) sum++; (d) for (i=0; i < n-1; i++) for (j=i+1; j <n; j++) { tmp = A[i][j]; A[i][j] = A[j] [i]; A[j][i] = tmp; (e) sum = 0; for (i=1; i<=n; i++) for (j=1; j<=n; j+=2) sum++;
Give a big-Oh characterization, in terms of n,of the running time for each of the following...
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...
1- Find the time complexity of the following program, where n is given as input: i...
1- Find the time complexity of the following program, where n is given as input: i = n; while (i > 1) { j = i; while (j < n) { k = 0; while (k < n) { k += 2; } j *= 2; } i /= 2; } Express your answer using theta notation, and explain the amount of time it takes for each loop to finish.
(10') 6. For each of the following code blocks, write the best (tightest) big-o time complexity...
(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...
discrete math
(1) (15 pts) Time Complexity Analysis 1) (5 pts) What is the time complexity of the following code segment? Explain your answer; otherwise, you can't get full mark from this question. for(int i=1; i<n; i*=2) { sum-0; sum++; Answer: 2) (5 pts) What is the time complexity of the following code segment? Explain your answer; otherwise, you can't get full mark from this question. for(int j=0; j<n; j++){ for (int k=0; k<n; k++) { for (int =0; i<n;...
For each of the following six program fragments: a. Give an analysis of the running time (Big-Oh will do). b. Implement the code in the language of your choice, and give the running time for several values of N. Pseudo Code Implementation Analysis of runtime time (Big-Oh) (1) sum = 0; for(i = 0; i < n; ++i) ++sum; (2) sum = 0; for(i = 0; i < n; ++i) for(j = 0; j<n; ++i) ++sum; (3) sum = 0;...
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...
II. ALGORITHM COMPLEXITY AND ASYMPTOTIC ANALYSIS The below visual representations of iterative looping structures are provided for Question 3 through Question 20. Algorithm 1 Algorithm 2 log.n 256 Algorithm 3 Algorithm 4 n (10) Match one of our algorithms to the below code snippet. for (int i = 0; i <n; i++) { for(int j = 0; j<n; j++) { for (int k = 0; k<n; k++) { nop++; nop++; nop++; } } } for (int i = 0; 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...
Exercises • Determine running time for the following code fragments: (a) a = b + c; d = a + e; (b) sum = 0; for (i=0; i<3; i++) for (j=0; j<n; j++) sum++; (c) sum=0; for (i=0; i<n<n; i++) sum++; (d) for (i=0; i < n-1; i++) for (j=i+1; j <n; j++) { tmp = A[i][j]; A[i][j] = A[j] [i]; A[j][i] = tmp; (e) sum = 0; for (i=1; i<=n; i++) for (j=1; j<=n; j+=2) sum++;
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...
(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...
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