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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Test Automation Strategy and Roadmap | 15% | - Test Automation Planning - Test Automation Integration with CI/CD - Test Automation Governance - Test Automation Maintenance |
| Topic 2: Test Automation Validation | 15% | - Root Cause Analysis - Test Automation Assessment Metrics - Test Automation Verification |
| 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 - Success Factors for Test Automation - Purpose of Test Automation |
| Topic 5: Preparation for Test Automation | 15% | - Test Automation Architecture Design - Design for Testability and Automation - Rollout and Deployment Considerations - Test Automation Tool Evaluation and Selection - SUT Analysis for Test Automation |
| Topic 6: Execution and Implementation of Test Automation | 35% | - Logging and Reporting Strategies - Verifying Test Automation Solutions - Designing Test Automation Solutions - Developing Test Automation Solutions - Implementing Test Automation Solutions - Building Robust Automated Test Suites |
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NEW QUESTION # 31
A suite of automated test cases was run multiple times on the same release of the SUT in the same test environment. Consider analyzing a test histogram that shows the distribution of test results (pass, fail, etc.) for each test case across these runs. Which of the following potential issues is MOST likely to be identified as a result of such an analysis?
Answer: A
Explanation:
TAE recommends monitoring test results over repeated executions to detect non-determinism and flakiness. A histogram showing pass/fail distributions per test across multiple runs in the same environment and on the same SUT version is especially useful for identifying tests whose outcomes vary without corresponding changes. If a test sometimes passes and sometimes fails under equivalent conditions, the distribution reveals instability: repeated failures for the same test, intermittent patterns, or inconsistent outcomes compared with other tests that remain stable. This is a classic indicator of flaky tests or unstable test design (e.g., synchronization issues, hidden dependencies, data leakage, timing sensitivity) and is a key maintainability
/reliability concern in automation programs. While execution time outliers (A) require time-series or duration metrics rather than pass/fail distributions, a result histogram primarily focuses on outcome variability, not performance. Security vulnerabilities (B) are not identifiable from outcome distributions; they require static analysis, code review, or security testing methods. Maintainability issues (D) are generally inferred from code structure metrics (complexity, duplication), change frequency, or effort trends, not from pass/fail distributions across runs. Therefore, the most likely issue identified by analyzing such a histogram is unstable automated test cases.
NEW QUESTION # 32
In a first possible implementation, the automated test scripts within a suite locate and interact with elements of a web UI indirectly through the browsers using browser-specific drivers and APIs, provided by an automated test tool used as part of the TAS. In an alternative implementation, these test scripts locate and interact with elements of the same web UI directly at the HTML level by accessing the DOM (Document Object Model) and internal JavaScript code. The first possible implementation:
Answer: C
Explanation:
TAE describes "intrusiveness" as the degree to which automation reaches into internal implementation details of the SUT rather than interacting through externally visible, user-realistic interfaces. Using browser drivers and browser automation APIs exercises the UI similarly to a real user (via the browser's supported automation hooks), which is generally less intrusive than directly manipulating the DOM and internal JavaScript. Direct DOM/JS access can bypass real user interaction pathways, skip browser event chains, and depend on internal structures that are not part of the stable external contract. This increases the risk of false positives: tests may
"pass" by forcing UI states or reading internal values even when the application would not behave correctly for real users. Less intrusive automation (through browser-level drivers) tends to provide higher confidence that observed behavior reflects real user experience, reducing the chance that tests succeed while user-visible behavior is broken. TAE therefore associates lower intrusion with stronger validity of results and lower false- positive risk, especially for system/UI-level validation. While browser-driven automation can still be flaky for other reasons (timing, environment), in the specific comparison of interaction method, browser-driver-based execution is the less intrusive option and is less likely to create false positives than direct internal DOM/JS manipulation.
NEW QUESTION # 33
Some automated regression test scripts run by a TAS in a given test environment make calls to private APIs that require authentication for all requests (the authentication method is the same for all APIs). The SUT is a business-critical system. The following two changes are planned: a change in the authentication method of all APIs and a minor upgrade of the OS (Operating System) in the test environment. You have updated the test scripts to cope with the change in the API authentication method. Which of the following sequences of activities is BEST to ensure that the test scripts are not adversely affected by these changes?
Answer: A
Explanation:
TAE recommends controlled change management to isolate causes when multiple changes are introduced.
When you apply more than one change at once, diagnosing failures becomes harder because you cannot easily attribute effects to a specific change. The best practice is to implement changes incrementally, validating automation and system behavior after each change using a representative subset of tests (e.g., smoke/build verification or targeted regression) to quickly detect issues. Because the system is business-critical, risk mitigation is stronger: you want early detection and clear attribution. After each change is validated with a subset, you then execute the full updated regression suite to ensure overall coverage and confidence. Options A and C apply two changes before running tests, which reduces diagnostic clarity and increases the risk of late discovery. Option D describes incremental changes with subset testing but omits the final full-suite run, which TAE would recommend to ensure broad coverage after all changes have been applied. Therefore, the best sequence is: change one item, run a subset, repeat for the next change, then run all updated scripts.
NEW QUESTION # 34
Which of the following information in API documentation is LEAST relevant for implementing automated tests on that API?
Answer: C
Explanation:
To implement automated API tests, TAE emphasizes that testers need precise, actionable interface specifications: what endpoints exist, what inputs they accept, how to authenticate/authorize requests, and what outputs are returned (status codes, headers, response body schemas/formats). Options B, C, and D directly support test design and implementation: parameter details enable valid/invalid request construction and boundary coverage; authentication mechanisms are required to execute any protected calls and to test auth- related behaviors; response formats enable robust assertions (including schema validation). Release notes and change logs are valuable for understanding evolution, migration, and backward compatibility considerations, but they are not typically required to implement the tests for the current API behavior when the current specification is available. They may help explain why something changed or guide test updates over time, yet they are less directly relevant to writing the core automated checks compared with endpoint inputs, auth, and response structure. Therefore, among the options, past release notes/change logs are the least relevant for implementing automated tests on the API.
NEW QUESTION # 35
As a TAE, you are evaluating a test automation tool to automate some UI tests for a web app. The automated tests will first locate the required HTML elements on the web page using their corresponding identifiers (locators), then perform actions on those elements, and finally check the presence of any expected text for an HTML element. These tests are independent of each other and are organized into a test suite that must be run every night against the most recent build of the web app. There is a high risk that the web app will crash while running some automated tests. Based only on the given information, which of the following is your MOST important concern related to the evaluation of the test automation tool?
Answer: C
Explanation:
Given the explicit risk that the web app may crash during execution, the highest-priority tool capability is resilience: the ability to recover, continue, and provide usable results from unattended nightly runs. TAE emphasizes that automation must be reliable as a process, not just at the single-test level. If one crash aborts the entire suite, the organization loses feedback for many tests, reduces confidence in the pipeline, and increases triage cost. Therefore, capabilities such as automatic restart of the browser/app, test isolation, robust teardown, failure handling, skipping/marking affected tests, and resuming execution with proper reporting are critical evaluation criteria. Option A (descriptive meta-language) can help readability or non-coder authoring but is not the most urgent need based on the scenario. Option C (mock server) is useful for isolating dependencies in some test levels, but the scenario is UI tests against the most recent build; nothing indicates an API dependency problem that drives tool selection here. Option D (licensing feature sets) affects procurement, but it does not directly mitigate the stated operational risk. Hence, recovery and continuation support is the most important concern.
NEW QUESTION # 36
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