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testing techniques

This is a long survey paper on testing techniques, and we will spend a decent amount of time on it. The sections we will cover are: 1, 2 (not 2.1.2.C,D), 3 (not 3.3-3.6), 4, 5 (not 5.1.2, 5.1.3 only up to definition 5.2, not 5.2, not 5.3); we will not cover 6, but you should read the conclusion (section 7), and the appendix may help with terms. The questions below only deal with some of the introductory ideas (not even through all of Section 2.1), so you do not need to study the whole paper before answering the questions.

1. Page 368 describes two parts of the idea of test data adequacy, captured in Definitions 1.1 and 1.2. I will call the criterion function of Definition 1.1 C1 and that of 1.2 C2. Discuss the practical implications of having only one of C1 or C2. What would it mean in practice to only have available a tool that computed C1? C2? The paper also discusses a “stopping rule” Mr. Is such a rule always easy to write? Discuss issues in creating a stopping rule function, especially in a very large project.

2. Suppose I am the manager of a large software project and you are a developer who also creates tests. I decide that our delivery rule is that we will not deliver our project until we achieve 100% statement coverage in our in-house testing, and I ask if anyone on the team has any objections. Will you speak up with any objections? Why or why not? Be sure to give a good explanation for either decision you make.

The questions below are over Sections 3.1 and 3.2 in the Zhu et al. paper. We will not discuss these sections in class.

1. I want to stop testing when I believe there are no more than 10 real errors left in my system. Suppose I seeded 100 artifical errors in my system, and my testing has found 75 of them. What is the maximum number of real errors my testing could have found to convince me to stop testing now? (Compute, and explain your answer.) If you indeed only uncovered that many real errors during your testing, would you stop at this point? (Fully explain your answer.)

2. Could error seeding be applied iteratively? That is, could we use error seeding to reach a goal, then start again with the clean system and run another error-seeding testing phase? Would it be valuable? What would the difficulties be? (Explain your answers.)

3. What is the fundamental weakness of error seeding? With this weakness, would you use it if you were in charge of testing a software product? (Explain.)

4. Suppose I use mutation testing on my program P, and my test set is perfect, (meaning that every different mutant is rejected by my test set), but I do not know that my test set is perfect. I let my automated mutation testing system generate 10,000 mutants. According to the paper, what work will I have to do? How much work will I have? And how much time would you estimate that it will take me to do this? (Be sure to answer all parts; the last two parts must be answered quantitatively, with concrete numbers).

5. Explain the two assumptions behind mutation testing. Do you believe they are valid? (Explain why or why not.)

6. Would you use mutation testing if you were in charge of a project? (Explain.)

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