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Welcome to the Software Testing MCQs Page

Dive deep into the fascinating world of Software Testing with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Software Testing, a crucial aspect of Software Engineering. In this section, you will encounter a diverse range of MCQs that cover various aspects of Software Testing, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Software Engineering.

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Check out the MCQs below to embark on an enriching journey through Software Testing. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Software Engineering.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Software Testing. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Software Testing MCQs | Page 41 of 43

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Q401.
What is the reason for the uncertainty in the expected time of software failure?

a.

The programmer made errors

b.

The relation between the input and the order of instructions is not known

c.

Both a and b

d.

None of the above

Discuss
Answer: (c).Both a and b Explanation:The reason for the uncertainty in the expected time of software failure is that we do not know where the programmer made errors and the relation between a certain input and the order in which the corresponding set of instructions is being executed is not usually known.
Q402.
What is the purpose of modeling subsequent failures as a stochastic process?

a.

To determine the form and probability distribution of the random variables

b.

To predict the expected time of software failure

c.

To predict the number of failures in a certain time interval

d.

All of the above

Discuss
Answer: (a).To determine the form and probability distribution of the random variables Explanation:The purpose of modeling subsequent failures as a stochastic process is to determine the form and probability distribution of the random variables.
Q403.
What is the meaning of non-homogeneous Poisson process?

a.

The probability distribution remains constant over time

b.

The probability distribution changes over time

c.

The probability distribution remains constant over a finite time

d.

None of the above

Discuss
Answer: (b).The probability distribution changes over time Explanation:A non-homogeneous Poisson process is one whose probability distribution changes over time.
Q404.
What is the relationship between failure intensity function and the number of failures observed?

a.

Failure intensity function is independent of number of failures observed

b.

Failure intensity function increases with the number of failures observed

c.

Failure intensity function decreases with the number of failures observed

d.

None of the above

Discuss
Answer: (c).Failure intensity function decreases with the number of failures observed Explanation:The failure intensity function decreases as the number of failures observed increases, assuming a (partly) successful effort to repair the underlying errors.
Q405.
What is the basic execution time model (BM)?

a.

The decrease in failure intensity is independent of the number of failures observed

b.

The decrease in failure intensity is proportional to the number of failures observed

c.

The decrease in failure intensity is constant as a function of the number of failures observed

d.

None of the above

Discuss
Answer: (c).The decrease in failure intensity is constant as a function of the number of failures observed Explanation:In the basic execution time model (BM), the decrease in failure intensity, as a function of the number of failures observed, is constant.
Q406.
What is the difference between the basic execution time model (BM) and the logarithmic Poisson execution time model (LPM)?

a.

BM and LPM have the same form of the failure intensity function

b.

BM and LPM have different forms of the failure intensity function

c.

BM and LPM do not consider the failure intensity function

d.

None of the above

Discuss
Answer: (b).BM and LPM have different forms of the failure intensity function Explanation:The basic execution time model (BM) and the logarithmic Poisson execution time model (LPM) differ in the form of the failure intensity function.
Q407.
How many parameters does the BM model have?

a.

1

b.

2

c.

3

d.

4

Discuss
Answer: (b).2 Explanation:The BM model has two parameters: λ₀ and v₀.
Q408.
What is the definition of operational profile?

a.

The set of possible input classes and the probabilities that input from those classes is selected

b.

The set of possible input classes and the amount of time each input class is selected

c.

The set of possible input classes and the number of instructions executed for each input class

d.

The set of possible input classes and the number of failures for each input class

Discuss
Answer: (a).The set of possible input classes and the probabilities that input from those classes is selected Explanation:The set of possible input classes together with the probabilities that input from those classes is selected
Q409.
What is the shape of the failure intensity curve in case of a strong non-uniform operational profile?

a.

Linear

b.

Convex

c.

Concave

d.

S-shaped

Discuss
Answer: (b).Convex Explanation:In case of a strong non-uniform operational profile, the failure intensity curve will have a convex shape.
Q410.
What is the relationship between the failure intensity and mean failures in both BM and LPM models?

a.

Failure intensity is a constant while mean failures is a function of execution time

b.

Failure intensity is the derivative of mean failures

c.

Failure intensity is the integral of mean failures

d.

Mean failures is the derivative of failure intensity

Discuss
Answer: (b).Failure intensity is the derivative of mean failures Explanation:In both BM and LPM models, mean failures is a function of execution time and failure intensity is the derivative of mean failures.
Page 41 of 43

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