Question

JAVA - algorithm analysis and sorting

Question 1

Which of the following features grows fastest?

1. N²

2. log N

3. N log N

4. N

5. 10

Question 2

Given the following code segment:

for( int i = 1; i < n; i++ )
  for( int j = 1; j < i; j++ ) 
    k = k + i + j; 

What is the runtime of the code segment?

1. None of the above 

2. O(i*N)

3. O(N²)

4. O(N⁴)

5. O(N)

Question 3

The runtime for the following code is:

for (i = 1; i <= n; i++) { 
    for (j = 1; j <= n-1; j++) { 
    k = k + i + j; 
  } 
}  
for (i = 1; i <= n; i++) { 
   m = m + i; 
}

1. O(N² + N)

2. O(N³)

3. O(N)

4. O(N²)

Question 4

Analyzing algorithm efficiency is

1. To estimate execution time

2. To measure exact execution time

3. To find the average driving time

4. To estimate the degree of growth in the form of a function

Question 5

Which of the following complexities is nlogn

1. 23nlogn + 50

2. 23n + 68logn

3. 45n + 45nlogn + 503

4. 300n + 400n*n

5. n*n*n + nlogn

Question 6

The approach searches incrementally for a candidate. As soon as one finds out that this will not provide a solution, look for a new candidate.

The approach is called. ( several answers possible)

1. Backtracking

2. Recursion

3. Divide-and-conquer

4. Brute-force

5. Dynamic programming

Answer 1

Question 1
N2 features grows fastest
Answer:
1. N2

Question 2
Runtime of the code segment is O(N2)
Answer:
3. O(N2)

Question 3
Runtime of the code segment is O(N2)
Answer:
4. O(N2)

Question 4
Analyzing algorithm efficiency is To estimate the degree of growth in the form of a function
Answer:
4. To estimate the degree of growth in the form of a function

Question 5
23nlogn + 50, 45n + 45nlogn + 503 are of complexities nlogn
Answer:
1. 23nlogn + 50
3. 45n + 45nlogn + 503

Question 6
The approach searches incrementally for a candidate. As soon as one finds out that this will not provide a solution, look for a new candidate.
The approach is called Backtracking
Answer:
1. Backtracking