Here is class 12 computer science Unit 7 [Type B] solutions for Sumita Arora back exercise assignment. Below includes both textual and video solutions wherever required. View all the answers in assignment for chapter 7 and for all chapters here.

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## Q1: Calculate the run-time efficiency of the following program segment:

### Solution:

O(n) Due to the while loop having upper bound input i.e. n

## Q2: Calculate the run-time efficiency of the following program segment:

### Solution:

O(n^3) Due to the three nested while loop each having n and product of three loop i.e. n^3.

## Q3: If the function doIt() has an efficiency factor of 5n, calculate the run-time efficiency of the following program segment.

### Solution:

O(5n^2) Due to the nesting of the doIt() and having 5n in product with n for the while loop.

## Q4: If the efficiency of the function doIt() can be expressed as O(n)=n^2, calculate the efficiency of the following program segment.

### Solution:

O(n) = n^4 Due to the nested while loop having upper bound input i.e. n hence it gives n^2 in product with nested function doIt() having O(n) = n^2.

## Q5: If the efficiency of the function doIt() can be expressed as O(n)=n^2, calculate the efficiency of the following program segment.

### Solution:

O(n) = n^3 Due to the while loop having upper bound input i.e. n and the nested function doIt() having O(n) = n^2. Hence O(n) =n*n^2

## Q6: Given a list A of appropriate size, what is the complexity of the following code in terms of n?

### Solution:

O(n) = n As the while loop will execute for the n times because i is initialized with n in the starting.

## Q7: Given three lists A, B, C of appropriate sizes, what is the complexity of the following code in terms of n,m, and p?

### Solution:

O(n) = n*p*m The all three nested loop will be get product with upper bound to provide the complexity.

## Q8: Given integer variable x and a list A of appropriate size, what is the complexity of the following code in terms of n?

### Solution:

O(n) = logn As of the mid positioning property similar to binary search.

## Q9: Given a list A of appropriate size, what is the complexity of the following code in terms of n?

### Solution:

O(n) = 2n The two concatenate for loop of each upper bound n will be added to result the complexity. O(n) = n+n

## Q10: Given a list A of appropriate size, what is the complexity of the following code in terms of n?

### Solution:

O(n) = n^2

## Q11: Given a list A of appropriate size, what is the complexity in terms of n?

### Solution:

O(n) = n The while loop will execute for the n times as if bound has at most limit is n.

## Q12: Given integer variable x and a list A of appropriate size, what is the complexity of the following code in terms of n?

### Solution:

O(n) = logn As of the mid positioning property similar to binary search.

## Q13: Given a list A of appropriate size, what is the complexity in terms of n?

### Solution:

O(n) = 2n The two concatenate for loop of each upper bound n will be added to result the complexity. O(n) = n+n

## Q14: What is the time complexity of the following algorithms?

(i) Insertion Sort O(n^2) (ii) Binary Search O(logn) (iii) Linear Search O(n)

## Q15: Based on the complexity analysis, which sorting algorithm is more efficient and why?

Binary sort will be a good option as of having O(logn) time complexity than the other mentioned options.

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