Which type of testing is done when one of your existing functions stop working?

1 answer:

6 0

The answer to the question is "alpha testing". Alpha testing aims to address issues like errors and debugging before software is launched. This testing is performed by developers when problems arise. In the software testing process, alpha testing occurs first, followed by beta testing. During alpha testing, developers check existing modules or functions that may have malfunctioned, ensuring any detected errors are addressed.

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Exercise 8.1.9: Diving Contest Your school is hosting a diving contest, and they need a programmer to work on the scoreboard! Yo

zubka84 [942]

Response:

def calculate_score(theTuple):

first, second, third = theTuple

if first >= 0 and first <=10 and second >= 0 and second <=10 and third >= 0 and third <=10:

print(first + second + third)

else:

print("Range must be 0 to 10")

Clarification:

This line initiates the function

def calculate_score(theTuple):

This line extracts the values used in the function

first, second, third = theTuple

The subsequent if statement verifies whether the values fall within the 0 to 10 range

if first >= 0 and first <=10 and second >= 0 and second <=10 and third >= 0 and third <=10:

This computes the total score

print(first + second + third)

else:

Should the scores be outside the 0 to 10 limits, this line will be executed

print("Range must be 0 to 10")

4 0

23 days ago

You are a police officer trying to crack a case. You want to check whether an important file is in the evidence room. Files have

Harlamova29_29 [932]

Answer:

Since RANDY operates randomly, any file within the specified index range will have the recurrence relation as follows:

T(n) = T(n-i) + O(1)

Here, the probability is 1/n, where i can vary between 1 and n. The variable n in T(n) denotes the size of the index range, which will subsequently reduce to (n-i) in the following iteration.

Given that i is probabilistically distributed from 1 to n, the average case time complexity can then be expressed as:

T(n) = $\sum_{i=1}^{n}\frac{1}{n}T(n-i) + O(1) = T(n/2)+O(1)$

Next, solving T(n) = T(n/2) + O(1)

yields T(n) = O(log n).

Thus, the complexity of this algorithm is O(log n).

It should be noted that this represents the average time complexity due to the algorithm's randomized nature. In the worst-case scenario, the index range may only decrease by 1, resulting in a time complexity of O(n) since the worst-case scenario would be T(n) = T(n-1) + O(1).

3 0

1 month ago

Read 2 more answers

Leah Jones is the IT manager at Rock Solid Outfitters, a medium-sized supplier of outdoor climbing and camping gear. Steve Allen

Natasha_Volkova [897]

Answer:

Step 1: Create a table reflecting the three potential scenarios and two possible outcomes. There should be a total of 8 distinct rules for the three varying conditions, structured similarly to the discount table shown here in the example: attached is the discount table

Step 2: The rules can now be made simpler by taking the following aspects into account:

a) When a consumer completes the survey form AND opts into the newsletter, according to Rules 1 and 2, they qualify for a discount if their order exceeds $100. This leads to two distinct rules being formulated while the third condition (order quantity) holds significance.

b) If the buyer fills out the survey form OR subscribes to the newsletter, as indicated by Laws 3, 4, 5, and 6, they will benefit from free shipping, regardless of the order amount. As a result, this situation can be divided into two individual rules, where at least one requirement is satisfied, but not both.

c) When a customer fails to meet any requirements, corresponding to Rules 7 and 8, the order value will not qualify for either free shipping or discount. This can be seen as a single law. The linked simplification table illustrates this.