CTAL-TTA Certified Tester Advanced Level Technical Test Analyst Question and Answers

Including security testing in a test approach is valid when there are concerns about unauthorized access or activities, such as the threat of unauthorized copying of applications or data (option A). This type of testing aims to uncover vulnerabilities that could be exploited to compromise the confidentiality, integrity, or availability of the system. The other options listed—availability measurements (option B), system's peak load handling (option C), and frequent software changes (option D)—relate to different aspects of testing, such as reliability, performance, and maintainability, which are not directly associated with security testing.

In portability testing for a video game that is anticipated to be highly popular, the key area to emphasize is installability. This involves ensuring that the game can be successfully installed across different platforms and configurations that potential players might use. Focusing on installability helps minimize technical barriers to entry, crucial for a successful launch and widespread adoption of the game .

Failure Mode and Effect Analysis (FMEA) is a structured approach to identify and address potential failures in a system, product, process, or service. The major factors involved in calculating risk priorities in FMEA are typically the severity of the potential failure, its likelihood of occurrence, and the ability to detect it. These factors are usually combined to form a Risk Priority Number (RPN) for each potential failure mode identified. However, the specific factors mentioned in the options like functionality, reliability, usability, maintainability, efficiency, and portability are quality characteristics that could be considered in an FMEA analysis but are not directly used for calculating risk priorities. Likewise, financial damage, frequency of use, and external visibility might influence the severity or impact of a failure, but they are not standard factors in calculating risk priorities in the context of FMEA. Therefore, the most relevant factors for calculating risk priorities in an FMEA context would typically be the likelihood of the failure occurring and its potential impact, which aligns with option C: Likelihood and impact.

It's important to note that while these explanations are based on general principles and practices related to fault seeding and FMEA, the specifics might vary slightly in different contexts or with different methodologies.

Test automation extends beyond just automating the test execution process; it also includes setting up and managing test environments and may involve configuring hardware, software, network settings, and other necessary services to enable comprehensive and effective testing. This holistic approach is crucial for maintaining consistency and reliability in testing across different stages and conditions .

In the data flow analysis of the pseudocode, the variable output presents a potential anomaly. Initially, output is set to input1, but it may be overwritten if input2 is greater. The anomaly, specifically a 'definition-use' (du-path) issue, arises because there might be scenarios where output does not adequately reflect changes depending on the dynamic data flow influenced by the conditional. Proper testing and validation of such conditional structures are crucial to ensure that output consistently represents the largest of the two inputs as intended.

A generic risk factor that a Technical Test Analyst must consider is the integration of new technology into a product. This is because new technologies can introduce complexities and unknowns in performance, compatibility, and security, which can impact the overall quality and reliability of the product. Evaluating such integration risks is crucial for preparing effective test strategies and ensuring that the product meets its intended functionality and quality standards​​.

To achieve 100% decision coverage, you must ensure every decision in the code has been evaluated both to true and false. Given the code:

If x > y and z = 3 statement1 elseif z = 4 statement2 endif;

Two tests are required:

• Test 1: Set x > y true and z = 3 to evaluate the first decision as true and execute statement1.
• Test 2: Set z = 4 (ensuring the first condition x > y and z = 3 evaluates to false) to evaluate the elseif condition as true and execute statement2.

This testing ensures that both branches of the decision have been evaluated.

Once existing test cases have been identified for refactoring, the next step is typically to make changes to the internal structure of these tests to improve their maintainability. This involves revising the code or scripts to make them cleaner, more efficient, and easier to understand, which helps in maintaining them over time as the software evolves. This process may also involve updating test data or dependencies to ensure that the tests remain robust and reliable .

The true statement about test automation, particularly in contexts aiming for continuous deployment, is that increasing automation levels is generally pursued to increase deployment frequency. Automated tests can be executed faster and more frequently than manual tests, thereby supporting rapid iterative development and continuous integration practices. This accelerates the overall software development process, allowing for quicker deployments to production .

According to the INVEST criteria, the Testable and Small criteria have not been satisfied for the user story provided. Option B is correct.

• INVEST Criteria: The INVEST model stipulates that user stories should be Independent, Negotiable, Valuable, Estimable, Small, and Testable.
• Analysis of the User Story: The scope of the user story and its acceptance criteria suggests it is too broad (thus not 'Small') and the details provided, especially regarding response times and system notifications, imply potential challenges in effectively testing the story (thus possibly not 'Testable') without further refinement or breaking down the story into smaller, more manageable pieces.

The size and complexity of the requirements indicate that the story might be better classified as an epic, needing decomposition into smaller, more specific user stories that can be more feasibly addressed within agile iterations .

The earliest stage in the application's SDLC at which performance efficiency testing can be performed is during requirements analysis. At this stage, performance requirements and goals are established, providing a baseline for what needs to be tested and verified throughout the later stages of development​​.

Stress testing is the most appropriate method for identifying weak areas in code that may cause performance issues, especially under conditions of extreme load or stress. This type of testing deliberately pushes the system beyond its normal operational capacity to see how it behaves under stress, which can help reveal vulnerabilities in error recovery and transactional integrity that are not apparent under normal conditions. Stress testing can provide early insights into potential failure points and help prioritize areas for improvement before full-scale deployment​​.

The pseudo-code provided for the "Win" program reads in variables A, B, C, and D. However, only variables A, B, and C are used in the conditional statements to determine if the output will be "Win" or "Loose". Variable 'D' is never used after it is read, which is a classic example of a 'defined but not used' data flow anomaly. This means that while there is an instruction to read a value into variable 'D', there is no subsequent use of this variable in the program's logic or output.

Upon analyzing the control flow diagram provided, there are four distinct paths through the program, considering the flow between decision points and actions. Each path represents a unique sequence of execution through the system logic, dictated by the decision outcomes at various points. This information is critical for ensuring comprehensive testing coverage, as each path may expose different behaviors or outcomes in the application​​.

Quantitative Questionnaires are the best elicitation technique for questioning a large number of stakeholders specifically to obtain information for non-functional acceptance criteria. This method allows for collecting measurable, numerical data from a broad audience efficiently, which is crucial for understanding and defining non-functional requirements such as performance, scalability, and usability

An effective review preparation by a Technical Test Analyst includes ensuring that participants are well-prepared and that they spend enough time on preparation, which can be managed by checking the rate (option A). The use of review checklists (option C) and providing review training (option D) are also methods that contribute to more effective review preparation. However, managing the logging rate (option B), or the number of defects logged per minute during the meeting, is not related to the preparation phase but rather to the defect detection and logging phase during the actual review meeting. It is not a preparation activity but a review execution activity.

In Agile projects, test cases may need to be refactored to make them simpler and less costly to modify. This is crucial because Agile methodologies prioritize adaptability and frequent changes to the codebase and documentation. Refactoring test cases in this context ensures that they remain aligned with the continuously evolving project requirements, are easier for teams to manage, and can be quickly adjusted to accommodate new or changed functionality without significant rework costs .

In addressing the scenario described in the question, the primary considerations for choosing a test approach include the focus on overhauling the user interface, adding new features, and addressing customer complaints in a high-risk environment due to potential customer loss. A regression-averse strategy is also highlighted as critical due to significant changes in design and functionality.

Option D (2) is marked with ♦+ for Exploratory Testing (manual) and ♦ for Black-box Testing, with Test Automation marked as not to be used (−). This selection aligns best with the project's needs for several reasons:

• Exploratory Testing (Highly Recommended): This type of testing is crucial in Agile projects, especially when dealing with UI changes and new functionalities. Exploratory testing allows testers to interact with the system in ways that typical scripted testing may not cover, making it ideal for catching unforeseen issues in new interfaces and features.
• Black-box Testing (Recommended): This testing focuses on the functionality of the application without needing to understand the internal workings. Given the UI overhaul and feature additions, ensuring that the system behaves as expected from an end-user's perspective is necessary.
• Avoidance of Test Automation (Not to be Used): While automation is valuable, focusing primarily on manual testing techniques like exploratory testing is suggested for this specific release due to the extensive UI changes and the need for creative and intuitive testing approaches that adapt quickly to newly developed features.

By using Option D, the test approach supports the dynamic and user-focused nature of the release, addressing both the technical aspects of functionality and the user experience enhancements that are central to this overhaul .

The provided pseudo code for the Answer program shows a WHILE loop that will always execute because the condition for the loop to terminate (a >= d) is never met within the loop's body. This results in an infinite loop. Additionally, since the value of 'b' is initialized with 'a + 10' and 'a' starts from a value that is read and then set to 2, 'b' will never be equal to 12. Therefore, the 'THEN' branch of the IF statement, which includes 'print(b)', is unreachable. These are control flow anomalies because they represent logic in the code that will not function as presumably intended.

Service virtualization is used in test environments to simulate the behaviors, data, and performance characteristics of dependent systems that are not available for testing due to limitations such as cost, access, or complexity. This allows for more thorough testing of the product under test in a controlled, stable environment that mimics real-world conditions without the need for actual live systems .

A key practice in a regression-averse test approach is to increase automated test coverage. This strategy allows the testing team to cover more ground routinely and reliably with automated checks, thus freeing resources to focus on exploratory testing. Exploratory testing is crucial for uncovering issues in areas less well-served by scripted testing, particularly in complex or high-risk functionalities. This approach helps maintain a balance between routine regression checks and adaptive, risk-focused testing strategies .

Fault seeding and fault injection tools are used intentionally to introduce defects into a system or software to test the robustness of the test suite. This method helps in validating the effectiveness of the test processes and configurations by ensuring that the tests are capable of detecting and isolating inserted faults. It is a technique used to measure the quality of testing rather than debugging or performance compliance, which relates directly to the fundamental purpose of enhancing test coverage and the detection capability of the test suite .

The scenario written in correct Gherkin format and appropriate for the User Story described is Option D:

• Given that three Purchase Orders with a total value of £21.75 have been placed so far this month,
• When the Purchasing Manager requests the list of Purchase Orders placed this month,
• Then the 3 orders and their total value of £21.75 are displayed.

This scenario correctly uses the Gherkin syntax with Given-When-Then structures that clearly specify the context, the action taken by the user, and the expected outcome, making it directly relevant to the user story’s intent .

Static analysis is the best technique for identifying the root causes of issues in a legacy system where small functional enhancements take disproportionately long to implement. This technique involves examining the code without executing it to detect potential vulnerabilities, coding errors, and complexities. Static analysis can highlight problematic code segments and inefficient coding practices that may contribute to the increased time required for implementing changes, thereby assisting in addressing these systemic issues efficiently​​.

For a keyword-driven testing approach involving operations on an order number, the minimal essential columns for the input table would be 'Action', 'Order ID', and 'Expected Result'. This setup supports clearly defined operations (Action) on specific entities (Order ID) and validation against expected outcomes (Expected Result), thereby facilitating structured and efficient testing. This configuration provides the required information for executing actions and verifying outcomes without redundancy or ambiguity​​.

A service virtualization tool is used to simulate the behavior of specific components in heterogeneous component-based applications such as APIs, services, and third-party apps that are not readily accessible during development and testing stages. These tools help create stable, controllable, and predictable testing environments by mimicking the interactions with the missing components. This is particularly useful when dealing with server or network traffic log data to develop a shareable testing service that replicates the real systems' behavior without their actual implementations.

Analyzing the given pseudocode for potential anomalies in data flow:

Declare C, F, Z Decimal Set Z = 32 Read F Set C = (F-Z) * 5/9 Free C, F, Z Print F

The potential anomaly is with variable F. It is used after being freed, which typically indicates an error in managing the variable's lifecycle within the code.

• Explanation: Freeing a variable typically indicates that it is no longer available for use, but F is used after this operation, which could result in undefined behavior or errors.

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.

For Modified Condition/Decision Coverage (MC/DC), each condition within a decision must independently affect the decision's outcome. The provided sets of values need to be analyzed to ensure that each component of the decision ((A > B) or (C > D) and (E = F)) can independently influence the result of the combined expression. Set 3 includes variations for all variables that allow each condition to be tested both true and false independently while keeping the overall expression's outcome affected. This choice provides the most efficient path to achieving MC/DC with minimal tests.

A unit test being 'deterministic' means that whenever it is run under the same conditions, it should produce the same results. This characteristic is crucial for reliable, repeatable testing outcomes that are not influenced by external factors or previous test states .

The key context here is the challenge of managing limited resources, particularly ROM and RAM, due to severe restrictions on code size in consumer electronics. Lazy instantiation is a design pattern that defers the creation of an object until the first time it is needed. This approach can significantly reduce the application's memory footprint by avoiding unnecessary pre-allocation of memory, which is particularly valuable in systems where memory resources are constrained. In reviewing the architecture for such a system, it's crucial to ensure that objects are only created when necessary and that memory is optimally managed. Hence, the focus on lazy instantiation would be most important to ensure that the system uses resources efficiently and remains within the restricted code size.

To achieve multiple condition coverage with the least number of tests, the selected test data set must cover all possible combinations of the conditions (A > B) or (C > D) and (E = F). Set 2, where each condition has been tested in both true and false states across the minimal test set, is the most efficient way to ensure coverage. It triggers different paths in the code with minimal redundancy, ensuring that each unique path is verified.

Given the stakeholder information provided:

• Reliability is important because the system, while not business-critical, still needs a good MTBF to be successful in the market. This is directly mentioned in the stakeholder information.
• Portability is essential as the system is expected to run in multiple hardware environments and various network environments, with changes anticipated in the operational environments.

Security is not highlighted as a concern, and performance efficiency, while generally important, is less critical as the system is not used intensively and is not time-critical. Therefore, reliability and portability are the most relevant non-functional quality characteristics to test in this scenario.

Installability testing is usually conducted during the System Testing stage of the SDLC. It typically includes testing the installation process of the software to verify that it installs correctly across various systems and configurations. This type of testing often overlaps with functionality testing to ensure all functions are available post-installation, and usability testing to ensure that the installation process is intuitive and user-friendly.

• Explanation: System testing encompasses a broad spectrum of testing practices intended to validate the software in its entirety, ensuring it meets the specified requirements and is ready for operation.