CTFL_Syll_4.0 Exam Dumps : ISTQB Certified Tester Foundation Level (CTFL) v4.0

The correct outcome of a two-value boundary value analysis applied to the password length is the set of test cases represented by option D. Boundary value analysis is a test design technique that focuses on the values at the boundaries of an equivalence partition, such as the minimum and maximum values, or the values just above and below the boundaries. A two-value boundary value analysis uses two values for each boundary, one representing the valid value and one representing the invalid value. For example, if the valid range of values is from 4 to 7, then the two values for the lower boundary are 3 and 4, and the two values for the upper boundary are 7 and 8. The test cases in option D use these values for the password length, while also satisfying the other requirements of the password, such as containing at least one numeric character, one capital letter, and one lowercase letter. The test cases in option D are:

1RhT: a 4-character password that is valid

rSp53: a 5-character password that is valid

3N3e10: a 6-character password that is valid

8sBdby: an 8-character password that is invalid The test cases in the other options are incorrect, because they either use values that are not at the boundaries of the password length, or they do not meet the other requirements of the password. For example, the test cases in option A are:

1xA: a 3-character password that is invalid, but it does not contain a capital letter

aB11: a 4-character password that is valid

Pq1ZZab: a 7-character password that is valid

7iDD0a1x: an 8-character password that is invalid References: ISTQB Certified Tester Foundation Level (CTFL) v4.0 sources and documents:

ISTQB® Certified Tester Foundation Level Syllabus v4.0, Chapter 2.2.1, Black-box Test Design Techniques1

ISTQB® Glossary of Testing Terms v4.0, Boundary Value Analysis, Equivalence Partition2

The three-point test estimation technique is a method of estimating the test effort based on three initial estimates: the most optimistic, the most likely, and the most pessimistic. The technique uses a weighted average of these three estimates to calculate the final estimate, which is also known as the expected value. The formula for the expected value is:

Expected value = (most optimistic + 4 * most likely + most pessimistic) / 6

Using the given values, the expected value is:

Expected value = (6 + 4 * 30 + 54) / 6 Expected value = 30 person hours

However, the expected value is not the only factor to consider when estimating the test effort. The technique also calculates the standard deviation, which is a measure of the variability or uncertainty of the estimates. The formula for the standard deviation is:

Standard deviation = (most pessimistic - most optimistic) / 6

Using the given values, the standard deviation is:

Standard deviation = (54 - 6) / 6 Standard deviation = 8 person hours

The standard deviation can be used to determine a range of possible values for the test effort, based on a certain level of confidence. For example, using a 68% confidence level, the range is:

Expected value ± standard deviation

Using the calculated values, the range is:

30 ± 8 person hours

Therefore, the final estimate is between 22 person hours and 38 person hours, which is option A.

This answer is correct because product risks are risks that affect the quality of the software product, such as defects, failures, or non-compliance with requirements or standards. Project risks are risks that affect the project’s schedule, budget, resources, or scope, such as delays, cost overruns, skill gaps, or scope changes. In this case, [I] and [IV] are product risks, as they relate to the accessibility and security of the software product, which are quality attributes. [II] and [III] are project risks, as they relate to the delivery time and the test automation skills of the test team, which are project factors. References: ISTQB Glossary of Testing Terms v4.0, ISTQB Foundation Level Syllabus v4.0, Section 2.1.1.1