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ISQI ISTQB Certified Tester Advanced Level - Test Automation Engineering CTAL-TAE (Syllabus v2.0) Sample Questions (Q21-Q26):

NEW QUESTION # 21
(Which of the following answers describes the LEAST relevant concern in selecting suitable test automation tools for a test automation project?)

A. In the case of commercial test automation tools, what factors determine the licensing costs of these tools (e.g., in terms of the maximum number of users supported and whether the license type is fixed or floating)?
B. What is the degree of technical knowledge and skills within the test team to implement code-based test automation for the project (e.g., in terms of programming and design patterns)?
C. In the case of open-source test automation tools, are these tools released under permissive or restrictive licenses, and, if applicable, is it specified whether they can be modified and by whom?
D. Has the test team been formed with the different personalities of its members in mind, to ensure that the interaction between them is effective in achieving the objectives of the test automation project?

Answer: D

Explanation:
TAE tool selection focuses on factors that materially affect feasibility, total cost of ownership, and long-term sustainability of the Test Automation Solution (TAS): technical fit, skill fit, integration capability, licensing
/legal constraints, and cost model. Option A is directly relevant because the team's capability strongly influences whether a code-heavy tool and framework approach is realistic and maintainable. Option B is relevant because licensing constraints can affect usage rights, redistribution, modification, internal compliance, and legal risk-critical for tool adoption in many organizations. Option D is also highly relevant because commercial licensing costs and licensing models (named user vs. floating, execution limits, parallelism add-ons, feature tiers) impact budgeting and scaling, and therefore the project's viability. Option C, while important for general team effectiveness, is not a primary criterion for selecting automation tools; it does not describe tool capability, integration constraints, cost, or risk in a way that distinguishes one tool from another. TAE typically treats team collaboration/communication and roles as project and organizational concerns (e.g., governance and processes) rather than tool-selection criteria. Therefore, among the provided choices, "team personality mix" is the least relevant concern for choosing suitable test automation tools in a TAE-focused tool selection.

NEW QUESTION # 22
Consider a TAS implemented to perform automated testing on native mobile apps at the UI level, where the TAF implements a client-server architecture. The client runs on-premise and allows creation of automated test scripts using TAF libraries to recognize and interact with the app's UI objects. The server runs in the cloud as part of a PaaS service, receiving commands from the client, translating them into actions for the mobile device, and sending the results to the client. The cloud platform hosts several mobile devices dedicated for use by this TAS. The device on which to run test scripts/test suites is specified at run time. You are currently verifying whether the test automation environment and all other TAS/TAF components work correctly. Which of the following activities would you perform to achieve your goal?

A. Check whether the TAF libraries that the test scripts will use to recognize and interact with the app's UI objects (widgets) function as expected
B. Manage the infrastructure that hosts the server, including hardware, software updates, and security patches
C. Check whether the references to the device on which the given test scripts/test suites will be executed are correctly hard-coded within these test scripts/test suites
D. Check whether all test scripts that will be executed by the TAS as part of a given test suite have expected results

Answer: A

Explanation:
The task is to verify the test automation environment and TAS/TAF components, not to validate the correctness of specific test suites. In a client-server TAF for mobile automation, a critical component is the automation library layer that exposes functions to locate and interact with UI objects, and that communicates with the cloud server/device farm. TAE guidance highlights that environment verification should focus on ensuring that the automation tooling stack can reliably perform its fundamental operations: connect to the execution infrastructure, select target devices at runtime, execute commands, and receive results. Checking that the TAF libraries correctly recognize and interact with widgets directly validates that the end-to-end automation mechanism (client # server # device # response) is functioning. Option A is not appropriate because the server is on PaaS; infrastructure management is typically handled by the provider and is not part of validating your TAS operation. Option B is incorrect because the scenario states the device is specified at run time, so hard-coding device references is not the expected design and is not the right verification focus.
Option D concerns test suite correctness (expected results), which is a later step after confirming the automation environment works. Therefore, verifying that the TAF libraries function as expected is the correct activity.

NEW QUESTION # 23
An automated test script makes a well-formed request to a REST API in the backend of a web app to add a single item for a product (with ID = 710) to the cart and expects a response confirming that the product is successfully added. The status line of the API response is HTTP/1.1 200 OK, while the response body indicates that the product is out of stock. The API response is correct, the test script fails but completes, and the message to log is: The product with ID = 710 is out of stock. Cart not updated. When this occurs, you are already aware that both the failed test and the API are behaving correctly and that the problem is in the test data. The TAS supports the following test logging levels: FATAL, ERROR, WARN, INFO, DEBUG. Which of the following is the MOST appropriate test logging level to use to log the specified message?

A. WARN
B. INFO
C. DEBUG
D. FATAL

Answer: A

Explanation:
TAE logging guidance focuses on making logs actionable while reflecting severity and intent. Here, the test failed due to an expected, non-system fault condition: the product is out of stock, which is a valid business- state response and confirms the API behaved correctly. The issue is that the test data (product availability) did not satisfy the test's precondition. This is not a fatal condition (FATAL) because execution continues and the overall system is not unusable. It is not best treated as ERROR either (not offered as an option here) because an error-level message usually indicates a defect, malfunction, or unexpected failure needing immediate engineering attention. INFO would be too low because it may be lost among normal run messages and does not adequately flag that the test outcome is affected by a precondition violation requiring action (e.g., reseeding data, choosing a different product ID). DEBUG is typically reserved for highly detailed diagnostic traces intended for deeper troubleshooting, not for highlighting a test-data problem affecting test validity.
WARN is intended for abnormal or noteworthy conditions that do not indicate a product defect but may require attention to maintain test reliability. Therefore, WARN is the most appropriate level.

NEW QUESTION # 24
(Which of the following statements refers to a typical advantage of test automation?)

A. On average, automated tests written at the API level are likely to run faster than automated tests written at the UI level
B. Automated tests can determine whether actual results match expected results, even for non-machine- interpretable results
C. Artificial intelligence can be used to help identify redundant tests within large, long-running automated regression test suites
D. Automated tests can allow defects to be detected earlier than manual tests because their execution times can be shorter

Answer: A

Explanation:
In the ISTQB Test Automation Engineer (TAE) body of knowledge, a core, typical advantage of test automation is faster feedback through efficient execution, especially when tests are implemented at lower levels (e.g., API/service) rather than through the UI. UI tests inherently traverse more layers (browser, rendering, client-side code, network timing, and often multiple back-end calls), so they tend to be slower and more brittle. API-level tests bypass most UI-related overhead and interact closer to business logic/services, reducing execution time and improving reliability. Option A is incorrect because many results (e.g., visual aesthetics, subjective usability, tone, or "looks right") are not reliably machine-interpretable without specialized approaches and still often require human judgment. Option C may be possible in some contexts, but "AI redundancy identification" is not a typical, foundational advantage emphasized as a standard automation benefit. Option D is misleading: early defect detection is mainly achieved by earlier and more frequent execution (e.g., CI) and shifting tests left, not merely because a single automated run is shorter than manual execution. Therefore, the most typical advantage presented is that API automation generally runs faster than UI automation.

NEW QUESTION # 25
(Which of the following statements about how test automation is applied across different software development lifecycle models is TRUE?)

A. In Agile software development, regardless of context (e.g., type of application to be developed, tools available), test automation must be based on the test automation distribution known as the test pyramid model
B. In Agile software development, automated regression test suites sometimes grow so large that they can become difficult to maintain, and thus, it becomes crucial to invest in test automation at multiple test levels
C. In a Waterfall model, automated tests are usually executed only during the last phase of the development lifecycle, but their implementation occurs in the early stages
D. Unlike Agile software development, where automated unit tests are written by developers, often in a test-first fashion, in a V-model, automated unit tests are written by testers as part of unit testing

Answer: B

Explanation:
TAE guidance emphasizes that Agile/iterative delivery drives frequent change and frequent regression risk, which often leads teams to expand automated regression suites over time. As suites grow, they can become slower, costlier to maintain, and harder to keep stable-especially if the suite is concentrated too heavily at the UI level. For this reason, TAE stresses investing in automation across multiple test levels (unit
/component, API/service, and selected UI), aligning with principles behind balanced automation strategies (often illustrated by the "test pyramid"). This directly supports option A. Option B is not generally true: in Waterfall/V-model, testing activities (including automation design and implementation) are planned and may start early, but execution and refinement occur across phases aligned with integration and system readiness- not "usually only during the last phase." Option C is too absolute: the test pyramid is a common heuristic, but TAE does not mandate it "regardless of context"; constraints like legacy systems, risk, architecture, and tooling can change the optimal distribution. Option D is incorrect because unit testing is typically a developer responsibility in both Agile and V-model contexts; testers may support, review, or contribute but do not
"write automated unit tests" as a defining V-model rule. Therefore, A best matches documented lifecycle realities and maintenance concerns.

NEW QUESTION # 26
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