CTAL-TTA Sample Questions Answers

In the context of an internet banking project where reliability and maintainability are emphasized, a key factor for maintainability is the modularity of the system. Implementing the user interface independently from other software modules (answer B) can significantly enhance maintainability. This is because it allows changes to be made to the user interface withoutimpacting the underlying business logic or data access layers, making the system more adaptable to change. This kind of separation of concerns is a recognized best practice in software design for maintainability. The other options (A, C, and D) relate more to reliability and security aspects than to maintainability.

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.

Model-based testing tools support the creation and execution of tests based on models of the system under test. Finite state machines (FSMs) are often used in model-based testing to describe the expected behavior of a system during execution. FSMs help in defining the states of the system and the transitions between these states based on events, which can then be used to generate test cases that validate the system's behavior against the model.

Maintainability metrics typically used with static analysis include measures that reflect the complexity and understandability of the code, such as Number of Lines of Code (LOC), Number of Function Calls, and Comment Frequency. These metrics help in assessing how easily the software can be understood, modified, and maintained. Mean Time Between Failures (MTBF), on the other hand, is a reliability metric. It measures the time elapsed between inherent failures of a system during operation. MTBF is used to predict the system's reliability and is not directly related to the maintainability of the code. Reliability metrics like MTBF would be used in the testing phase to measure the operational reliability of the system rather than during static analysis for maintainability assessment.

The statement about performance testing tools that is NOT correct is that they typically drive the application by simulating user interaction at the graphical user interface (GUI) level to more accurately measure response times. In practice, performance testing tools often simulate user interactions at a protocol or service level rather than the GUI level. This approach allows the tools to generate a high load by simulating many virtual users, which would be challenging to achieve with GUI-level interactions due to the higher resource consumption and slower execution speed associated with GUI automation.

Performance testing tools are designed to assess the performance of a system under a particular load and are not primarily focused on the user interface. They simulate multiple users accessing the system simultaneously, which helps in identifying bottlenecks, understanding the system's behavior under load, and determining how the system scales with increasing load. The tools typically simulate user requests to the server, bypassing the GUI to directly test the backend, APIs, or other service endpoints. This method allows for more efficient and scalable testing, enabling the simulation of thousands of users without the overhead of rendering the GUI.

When users complain about issues with links on a website, the most appropriate test tool to identify the causes of these failures is a hyperlink tool (answer B). Hyperlink tools are specifically designed to check the validity of links on web pages. They can automatically identify broken or dead links, which is essential for maintaining the quality and user experience of a website. Review tools, static analysis tools, and dynamic analysis tools do not primarily focus on hyperlink verification.

Cyclomatic complexity is a measure of the number of linearly-independent paths through a program's source code, which is often used as a measure of the complexity of a program. The control flow graph provided represents the logic of a software component and has more than 5 nodes with decision points, indicating that the complexity would exceed the maximum allowed value of 5. The calculation for cyclomatic complexity is V(G) = E - N + 2P, where E is the number of edges, N is the number of nodes, and P is the number of connected components. In this case, the calculated cyclomatic complexity exceeds the allowed threshold, thus a defect should be reported.

In the context of safety-critical systems, particularly in the medical domain, reliability is of utmost importance. For such systems, it is crucial to ensure that the software can handle unexpected input values and continue to operate without failure. This is essential to ensure patient safety and compliance with FDA requirements. Vulnerability scans (option A) are more related to security testing, whereas scalability (option C) and installation/de-installation (option D) are important but not specifically related to the reliability and safety criticality of the system in the medical domain.

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.

Reliability testing is aimed at verifying the software's ability to function under expected conditions for a specified period of time. It is typically conducted during system testing, where the software is tested in its entirety to ensure that all components work together as expected in an environment that closely simulates the production environment. Reliability testing is not typically associated with static testing, component testing, or functional acceptance testing, as these levels of testing do not address the overall behavior of the system over time.