CTAL-TTA Exam Dumps : Certified Tester Advanced Level Technical Test Analyst

Statements about Maintainability Testing:

A. It should start as soon as the draft design documents are available for review.

True. Maintainability testing can begin early in the development lifecycle, starting with reviews of design documents to ensure that maintainability concerns are addressed from the outset.

B. An application can be considered maintainable when static analysis and code review defects have been fixed.

False. While fixing defects identified by static analysis and code reviews improves maintainability, other factors such as documentation, ease of making changes, and regression testing must also be considered.

C. It tests the regression impact of software or environmental changes to an operational system.

False. This describes regression testing more than maintainability testing, which focuses on the ease of modifying the system and maintaining its performance.

D. It can be performed during Operational Acceptance Testing by multiple departments.

True. Maintainability testing can be part of operational acceptance testing (OAT), where different departments ensure that the system can be maintained and operated effectively.

E. It can be performed during User Acceptance Testing to ensure business processes can be maintained.

False. User acceptance testing (UAT) focuses on verifying that the system meets business requirements and user needs, not specifically on maintainability.

Correct Answer:

B. a and d

References:

The ISTQB CTAL-TTA syllabus and standard testing practices emphasize the importance of maintainability testing early in the lifecycle and its role in operational acceptance testing.

Sources:

ISTQB-CTAL-TTA Syllabus

General knowledge on maintainability testing practices.

When purchasing a simulator for performance testing, considerations should include:

Time to test the tool – How long it will take to validate the simulator itself.

Cost of hiring specialists – The financial aspect of requiring specialized knowledge to operate or customize the simulator.

Method and time to upgrade and retest the tool as the software changes – How the simulator can be kept up-to-date with the software it is meant to simulate and the effort involved in retesting it after updates.

These points focus on practical and economic aspects of using a simulator in testing environments.

To determine the percentage of decision testing coverage achieved by the given suite of test cases, we need to analyze the decisions and outcomes in the provided logic.

Detailed Analysis

Identify all decisions in the logic:

IF account number is valid

IF customer account is active

IF oldBalance < zero

IF balance now >= zero

IF account holder is VIP customer

Calculate the number of unique decisions:

There are 5 unique decision points in the logic.

Determine the possible outcomes for each decision:

IF account number is valid → 2 outcomes (True, False)

IF customer account is active → 2 outcomes (True, False)

IF oldBalance < zero → 2 outcomes (True, False)

IF balance now >= zero → 2 outcomes (True, False)

IF account holder is VIP customer → 2 outcomes (True, False)

Test Cases Analysis

Test Case A

Account number valid → True

Account is active → True

OldBalance = -100 → True (less than zero)

Balance now = +200 → True (greater than zero)

Not a VIP customer → False

Test Case B

Account number valid → True

Account is active → True

OldBalance = -100 → True (less than zero)

Balance now = -50 → False (less than zero)

Is a VIP customer → True

Coverage Calculation

To calculate the decision coverage, we need to see how many of the possible outcomes are covered by the test cases:

IF account number is valid (True in both A and B, False not tested)

IF customer account is active (True in both A and B, False not tested)

IF oldBalance < zero (True in both A and B, False not tested)

IF balance now >= zero (True in A, False in B, both outcomes tested)

IF account holder is VIP customer (False in A, True in B, both outcomes tested)

Out of the 10 possible outcomes (2 for each decision), the given test cases cover 6 outcomes:

Account number valid → True

Account number valid → False (not covered)

Customer account active → True

Customer account active → False (not covered)

OldBalance < zero → True

OldBalance < zero → False (not covered)

Balance now >= zero → True

Balance now >= zero → False

Account holder is VIP → True

Account holder is VIP → False

Thus, 6 out of the 10 outcomes are covered by the test cases, giving us a decision coverage percentage of:

Decision Coverage=(610)×100%=60%\text{Decision Coverage} = \left(\frac{6}{10}\right) \times 100\% = 60\%Decision Coverage=(106​)×100%=60%

References:

The sample questions and answers provided in the ISTQB CTAL-TTA documentation confirm this calculation method and the expected coverage percentage for similar logical scenarios​​​​​​.