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Otrada [13]
3 years ago
8

Consider two vectors that are NOT sorted, each containing n comparable items. How long would it take to display all items (in an

y order) which appear in either the first or second vector, but not in both, if you are only allowed LaTeX: \Theta\left(1\right)Θ ( 1 ) additional memory? Give the worst-case time complexity of the most efficient algorithm.
Computers and Technology
1 answer:
Darina [25.2K]3 years ago
7 0

Answer:

The correct answer to the following question will be "Θ(​n​2​)

". The further explanation is given below.

Explanation:

If we're to show all the objects that exist from either the first as well as the second vector, though not all of them, so we'll have to cycle around the first vector, so we'll have to match all the objects with the second one.

So,

This one takes:

= O(n^2)

And then the same manner compared again first with the second one, this takes.

= O(n^2)

Therefore the total complexity,

= Θ(​n​2​)

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Every recursive function should have an exit criterion (=handling the base case) to exit the recursion.

Without it, it wil recurse forever, until system resources run out (typically the call stack will overflow and your program will crash).

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a user has a large amount of data that she or he needs to store. the data will not be accessed regularly, but still needs to be
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A qualifier distinguishes the set of objects at the far end of the association based on the qualifier value.
Andrei [34K]

Answer:

True

Explanation: A qualifier is a term used in IT(information technology) and computer software. It is used to differentiate/ identify and select different sets of objects that are located at the far ends of a qualifier association.

A qualifier is usually used to identify an object from a set of closely related and similar objects, they are usually small boxes possibly with a rectangular shape.

7 0
3 years ago
Have you ever watched Full House? Who is your favorite character and why? EXPLAIN AND ILL GIVE BRAINLIEST!
liubo4ka [24]

Answer:

havent watched it and thanks for this

Explanation:

7 0
2 years ago
Greedy Algorithm Design
Alik [6]

Answer:

The algorithm is as follows:

1. Start

2. Get the number of items (n)

3. Get the current price of the n items (a1, a2..... an)

4. Get the possible hiked price of the n items (b1, b2..... bn)

5. Calculate the difference between the current and hiked prices for each item i.e. d_i = b_i - a_i

6. Sort the differences in descending order (i.e. from the greatest to the least)

7. Buy items in this order of difference

8. Stop

Explanation:

The algorithm is self-explanatory; however, what it does is that:

It takes a list of the current price of items (say list a)

E.g: a = [100, 150, 160]

Then take a list of the hiked price of the items (say list b)

E.g: b = [110, 180, 165]

Next, it calculates the difference (d) between corresponding prices d_i = b_i - a_i

d = [(110 - 100),(180-150),(165-160)]

d = [10,30,5]

Sort the difference from greatest to lowest (as the difference is sorted, lists a and b are also sorted)

d = [30,10,5]

a = [150, 100, 160]

b = [180, 110, 165]

If there is no hike up to item k, the couple would have saved (i = 1 to d[k-1])

Assume k = 3

The couple would have saved for 2 item

Savings = d[1] + d[2]

Savings = 30 +10

Savings = 40

The saved amount will then be added to the kth item in list a i.e. a[k](in this case k = 3) in order to buy b[k]

Using the assumed value of k

a[k] = a[3]

a[3] = 160

b[3] = 165

Add the saved amount (40) to a[3]

New\ Amount = 40 + 160

New\ Amount = 200

This new amount can then be used to buy b[3] i.e. 165, then they save the change for subsequent items

8 0
3 years ago
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