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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Test Automation Validation | 15% | - Root Cause Analysis - Test Automation Verification - Test Automation Assessment Metrics |
| Topic 2: Introduction and Objectives for Test Automation | 5% | - Success Factors for Test Automation - Risks and Benefits of Test Automation - Purpose of Test Automation |
| Topic 3: Preparation for Test Automation | 15% | - Test Automation Tool Evaluation and Selection - Rollout and Deployment Considerations - SUT Analysis for Test Automation - Design for Testability and Automation - Test Automation Architecture Design |
| Topic 4: Transitioning from Manual to Automated Testing | 15% | - Maintaining Automation Consistency - Criteria for Manual vs. Automated Testing - Automation Migration Strategies |
| Topic 5: Test Automation Strategy and Roadmap | 15% | - Test Automation Planning - Test Automation Maintenance - Test Automation Integration with CI/CD - Test Automation Governance |
| Topic 6: Execution and Implementation of Test Automation | 35% | - Developing Test Automation Solutions - Implementing Test Automation Solutions - Verifying Test Automation Solutions - Designing Test Automation Solutions - Logging and Reporting Strategies - Building Robust Automated Test Suites |
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NEW QUESTION # 41
You have agreed with your organization's managers to conduct a pilot project to introduce test automation.
Managers' expectations about the benefits of automation are too optimistic. Which of the following is LEAST relevant when deciding the scope of the pilot project's objectives?
Answer: B
Explanation:
TAE positions pilot projects as a controlled way to validate feasibility, calibrate expectations, and reduce adoption risk. Pilot objectives typically include assessing tool fit (technical compatibility, integration, reporting, maintainability), estimating realistic benefits and costs (execution speed, regression efficiency, coverage improvements, maintenance overhead), and assessing team readiness (skills, training needs, required roles). Those align directly with options A, B, and C. Network performance characteristics can matter for distributed test execution or remote environments, but evaluating enterprise network infrastructure at a deep level (availability, jitter, packet loss) is generally not a primary objective for a test automation pilot- especially when the central concern is overly optimistic expectations about automation benefits. A pilot should focus on demonstrating what can be automated, at what cost, with what stability and maintainability, and what process changes are needed. Infrastructure constraints may be observed as risks during the pilot, but a full network performance evaluation is more characteristic of IT operations or performance engineering initiatives, not a test automation introduction pilot scope. Therefore, option D is the least relevant when defining the pilot's objectives in a TAE-aligned approach.
NEW QUESTION # 42
An automated test case that should always pass sometimes passes and sometimes fails intermittently (non- deterministic behavior) when executed in the same test environment, even if no code (i.e., SUT code or the test automation code) has been changed. Which of the following statements about the root cause of this non- deterministic behavior is TRUE?
Answer: D
Explanation:
TAE treats non-deterministic (flaky) test behavior as a symptom that can originate from multiple sources:
timing and synchronization issues, race conditions, concurrency, environmental variability (resource contention, network latency), unstable test data, third-party dependencies, or hidden state leakage between tests. Because these causes often span boundaries-application code, infrastructure, deployment configuration, test tooling, and data pipelines-finding the true root cause frequently requires collaboration beyond the TAE role. Developers may need to inspect application logs, thread behavior, and recent architectural assumptions; system engineers may need to analyze resource saturation, container orchestration events, network anomalies, or environment drift. Option A is too specific and assertive: the root cause is not necessarily a race condition, and logs may not be sufficient to identify it. Option C is incorrect because no code change does not imply the environment is the only cause; flaky behavior can stem from hidden nondeterminism in the system or tests that is always present but only sometimes triggers. Option D is also incorrect; intermittent failures are often harder to diagnose than consistent deterministic failures because evidence is less reproducible. Therefore, the true statement is that determining the root cause may require support from developers and system engineers in addition to the TAE.
NEW QUESTION # 43
Which of the following descriptions of what some test automation tools can be used to do is TRUE?
Answer: D
Explanation:
TAE recognizes a range of supporting capabilities offered by test tools beyond pure scripted execution, including reporting, evidence capture, and run artifacts that help stakeholders understand what was tested.
Video recording of UI test sessions is a common feature in several UI automation ecosystems and cloud device
/browser platforms, used to provide visual evidence of steps performed, failures observed, and the application' s look-and-feel during execution. This supports debugging and communication with non-technical stakeholders. Option A overstates what test automation tools do: autonomously designing intuitive UIs and evaluating UX is largely outside typical test automation tool scope and requires human-centered design methods. Option C is also overstated: exploratory testing is inherently human-driven; tools can assist (session notes, heuristics support, telemetry) but do not truly conduct exploratory testing autonomously based on charters in the general TAE framing. Option B touches on advanced analytics and AI/ML-assisted quality insights; while some platforms offer risk prediction features, the phrasing implies broad predictive defect capability, which is not a standard, dependable tool function emphasized in TAE compared with concrete capabilities like artifact capture. Therefore, the clearly true, commonly supported capability is making video recordings of UI testing sessions.
NEW QUESTION # 44
You are currently conducting a Proof of Concept (PoC) aimed at selecting a tool that will be used for the development of a TAS. This TAS will exclusively be used by one team within your organization to implement automated UI-level test scripts for two web apps. The two tools selected for the PoC use JavaScript
/TypeScript to implement the automated test scripts and offer capture and playback capabilities. Three test cases for each of the two web apps were selected to be automated during the PoC. The PoC will compare these two tools in terms of their effectiveness in recognizing and interacting with UI widgets exercised by the test cases, to quickly determine whether test automation is possible and which tool is better. Which of the following TAFs is BEST suited for conducting the PoC?
Answer: D
Explanation:
For a PoC whose primary goal is rapid feasibility assessment and tool comparison (especially around object recognition and interaction), TAE recommends minimizing framework complexity and upfront engineering.
In a PoC, you want the shortest path to executing representative tests so you can observe tool behavior, stability, locator robustness, synchronization support, and ease of driving the UI widgets in scope. A one-layer approach-simple test scripts with minimal abstraction-reduces the time spent building reusable libraries, enforcing architecture, or creating business layers that are not necessary for answering the PoC question.
Multi-layer frameworks (two-layer and beyond) are more appropriate when you are establishing maintainability, reuse, and scaling for long-term automation. Those benefits matter in the full TAS implementation, but they can distort PoC outcomes by introducing additional design decisions, patterns, and glue code that hide or compensate for tool limitations. Since only six test cases are being automated and the objective is to quickly determine whether UI automation is possible and which tool performs better at widget interaction, the simplest structure (one-layer TAF) is best aligned with TAE PoC guidance: rapid learning, minimal overhead, and clear attribution of outcomes to the tool rather than to framework design.
NEW QUESTION # 45
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?
Answer: D
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 # 46
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