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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Preparation for Test Automation | 15% | - Test Automation Tool Evaluation and Selection - SUT Analysis for Test Automation - Rollout and Deployment Considerations - Design for Testability and Automation - Test Automation Architecture Design |
| Topic 2: Test Automation Strategy and Roadmap | 15% | - Test Automation Planning - Test Automation Governance - Test Automation Integration with CI/CD - Test Automation Maintenance |
| Topic 3: Transitioning from Manual to Automated Testing | 15% | - Maintaining Automation Consistency - Automation Migration Strategies - Criteria for Manual vs. Automated Testing |
| Topic 4: Introduction and Objectives for Test Automation | 5% | - Risks and Benefits of Test Automation - Purpose of Test Automation - Success Factors for Test Automation |
| Topic 5: Test Automation Validation | 15% | - Test Automation Verification - Root Cause Analysis - Test Automation Assessment Metrics |
| Topic 6: Execution and Implementation of Test Automation | 35% | - Implementing Test Automation Solutions - Designing Test Automation Solutions - Building Robust Automated Test Suites - Logging and Reporting Strategies - Verifying Test Automation Solutions - Developing Test Automation Solutions |
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NEW QUESTION # 80
(Which of the following aspects of "design for testability" is MOST directly associated with the need to define precisely which interfaces are available in the SUT for test automation at different test levels?)
Answer: D
Explanation:
In TAE, "design for testability" includes attributes that make it easier to create, execute, and maintain automated tests across levels (component, integration, system, UI). The need to define precisely which interfaces are available at different test levels-e.g., public APIs, service endpoints, message queues, UI automation hooks, test seams, logs, and internal test interfaces-maps most directly to architecture transparency. Architecture transparency concerns how clearly the system's structure, layers, and accessible interfaces are documented and exposed so test automation can reliably connect to the right interaction points.
This includes understanding which interfaces are stable, supported, and appropriate for each level of testing, and avoiding "guesswork" that increases brittleness. Controllability is about the ability to set inputs, states, and preconditions (e.g., reset data, seed databases, drive system state). Observability is about the ability to see outputs, internal states, and logs to assess outcomes. Autonomy concerns whether tests can run independently without external dependencies or manual intervention (e.g., isolated environments, stable test data). While controllability/observability/autonomy are critical for automation, the specific emphasis on "precisely defining which interfaces are available" is fundamentally an architectural transparency issue: clear interface availability and documentation enable correct, maintainable automation connections across test levels.
NEW QUESTION # 81
Which of the following is the BEST example of how static analysis tools can help improve the test automation code quality in terms of security?
Answer: A
Explanation:
TAE highlights that test automation code can introduce security risks, particularly when it handles secrets (API keys, passwords, tokens), test accounts, and connections to production-like systems. Static analysis tools can scan source code for insecure patterns and policy violations without executing the code. A common, high- impact security issue in automation is hard-coded credentials or secrets embedded in scripts, configuration files committed to version control, or test utilities. Detecting these is a direct security-quality improvement: it reduces exposure risk and supports compliance. Option A is incorrect because static analysis can produce false positives; detection heuristics are not perfect. Option B is useful for maintainability (duplication), but it is not specifically a security improvement example. Option D overclaims: static analysis cannot guarantee the absence of security vulnerabilities; it can only detect certain classes of issues. Therefore, the best security- focused example is that static analysis can identify hard-coded credentials and other sensitive data exposure in test automation code.
NEW QUESTION # 82
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?
Answer: D
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 # 83
A release candidate of a SUT, after being fully integrated with all other necessary systems, has successfully passed all required functional tests (90% were automated tests and 10% were manual tests). Now, it is necessary to perform reliability tests aimed at evaluating whether, under certain conditions, that release will be able to guarantee an MTBF (Mean Time Between Failures) in the production environment higher than a certain threshold (expressed in CPU time). Which of the following test environments is BEST suited to perform these reliability tests?
Answer: D
Explanation:
Reliability testing (e.g., long-duration runs, endurance/soak, stability measurements, MTBF assessment) requires an environment that closely resembles production in terms of configuration, resource allocation, deployment topology, integrations, and operational characteristics. TAE guidance emphasizes that measurements like MTBF are highly sensitive to environmental differences such as CPU quotas, background load, database sizing, network topology, virtualization settings, and monitoring agents. A local development environment is unsuitable because it is not representative, is often unstable, and typically lacks full system integration. A build environment focuses on building/packaging and fast verification, not production-like reliability evaluation. An integration environment can validate that systems work together, but it is frequently shared, changes often, and may not match production sizing and operational constraints; it is also commonly disrupted by other teams' deployments. Preproduction (often called staging) is designed to be the closest safe approximation to production while still allowing controlled testing, including reliability and performance- related evaluations, without risking real users or live data. Therefore, preproduction is the best-suited environment to run reliability tests intended to predict production MTBF behavior with credible confidence.
NEW QUESTION # 84
Which one of the following answers does NOT refer to an example of configuration item(s) that should be specified in development pipelines to identify a test environment (and its specific test data) associated with a web app under test on which to execute automated tests?
Answer: C
Explanation:
In TAE guidance, pipeline configuration items used to identify a specific test environment (and its associated test data) are those that uniquely define where the SUT is running and how automation connects to the deployed system and its dependent services and data stores. That typically includes the base URL of the deployed web application, endpoints/URLs for backend services used in that environment, and connection details to environment-specific databases (or references to secrets/credentials that enable those connections).
These items allow the same automated tests to be executed against different environments by switching configuration rather than changing test code. By contrast, "the number and type of automated tests to execute" is a test selection/execution configuration decision (what to run), not an environment identification configuration (where to run). You can run different subsets of tests in the same environment without changing the environment identity. TAE distinguishes environment configuration (addresses, endpoints, credentials, data sources) from orchestration configuration (suite selection, tags, parallelism). Therefore, option A does not describe a configuration item that identifies the test environment and its specific test data.
NEW QUESTION # 85
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