ISTQB CTAL-TTA Practice Test - Questions Answers, Page 6

A Technical Test Analyst during a product risk analysis would consider the complexity of new technology as a generic risk factor. Complex new technology can introduce uncertainties and potential issues that may not be well-understood, which can increase the risk of defects. Frequency of use, visibility of failure, and high change rate of business requirements are also valid considerations, but they are more specific to particular scenarios or aspects of the product rather than the generic technological complexity which is always a concern regardless of the context.

For a project where the reuse of software components is a key objective, it is essential to ensure that all modules, data, and interfaces are uniquely identified. This facilitates the tracking, maintenance, and reuse of these components in different parts of the software or in other projects. Unique identification helps in preventing confusion and conflicts that may arise due to the reuse of components that have the same name but different functionalities or interfaces.

100% statement coverage means that every line of code is executed at least once during testing. Based on the provided pseudo-code and the test cases given:

Test 1 executes the MIN = B statement when A and B are equal.

Test 2 executes the MIN = A statement and skips the inner IF since B is not equal to 2*A.

All statements within the code have been executed by these two tests, hence no additional test cases are needed to achieve 100% statement coverage.

Reliability testing is the process of checking whether the software consistently performs according to its specifications. For a commercial system with a critical internet-based user interface, ensuring that the application can handle connection failures without abnormal terminations is essential. Reliability testing would include testing the system's ability to recover from failures and continue operating, which directly addresses the risk identified.

Modified condition/decision coverage (MC/DC) requires each condition in a decision to be shown to independently affect the decision's outcome. For the code fragment provided, we have three independent conditions that need to be evaluated both as true and false. The minimum number of test cases needed to satisfy MC/DC for three conditions is four, which would allow each condition to be shown to independently affect the outcome of the decision.

The control flow graph provided illustrates the decision points for an airline's upgrade and boarding process. Decision coverage is a measure of the percentage of decision points executed during testing:

Test 1 covers the decision points: Gold card? (Yes) and Business full? (No).

Test 2 covers: Gold card? (No) and Economy full? (No).

Test 3 covers the decision that leads to being bumped from the flight, which is Economy full? (Yes) and Business full? (Yes).

From the given tests, the decision points for Gold card? (No) and Business full? (No) are not tested, leaving us with 4 out of 6 decision points covered, which is approximately 67% decision coverage.

The comment frequency in a code fragment relates to the number of comments in relation to the code size. A good level of comment frequency can significantly contribute to the maintainability of the software. Maintainability is a non-functional quality characteristic that refers to the ease with which a software system can be modified to correct defects, update features, improve performance or other attributes, or adapt to a changed environment. Comments in the code help developers understand the logic, purpose, and functionality of the code, which is crucial when modifications are required. This does not directly contribute to portability, usability, or performance efficiency, which are concerned with different aspects of the software's operation and user interaction.

Performance testing is a key part of ensuring that a system can handle the expected load and perform well under high demand. This type of testing is designed to test the robustness, speed, scalability, and stability of the system under a given workload. It is not primarily concerned with security threats such as code insertion (Option A), nor with fault tolerance in terms of unexpected input values (Option B), nor with the speed of addressing user-reported defects (Option C), although these may be tangential benefits. Performance testing is focused on ensuring that the system meets performance criteria and can handle increasing loads without degradation of service, which is essential for providing a good user experience and for the system's reliability.

Keyword-driven test automation is a framework where test cases are written using keywords that represent the actions or tests to be performed on the system. This is an extension of data-driven test automation, which focuses on separating test scripts from the test data, allowing the same test script to be run with various sets of data. Keyword-driven test automation further abstracts the process by allowing tests to be written in a more human-readable form that corresponds to business processes. This approach can improve maintainability and readability of test cases, making them easier to understand and modify. It's not necessarily the case that one is more maintainable or easier to develop than the other (Options C and D); rather, they serve different purposes in test automation strategy.