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| Section | Weight | Objectives |
|---|---|---|
| Reporting and Metrics | 12% | - Defining relevant automation metrics - Collecting and analyzing data - Visualization and dashboards - Reporting to stakeholders |
| Continuous Improvement | 19% | - Adapting to new technologies and requirements - Streamlining and maintaining test assets - Upgrading tools and frameworks - Refactoring and optimizing automation |
| Implementing Test Automation | 11% | - Developing and maintaining automation components - Handling synchronization, stability and reliability - Planning and running pilot projects - Managing technical debt |
| Introduction and Objectives for Test Automation | 5% | - Purpose, benefits and limitations of test automation - Test automation in software development lifecycle models - Roles and responsibilities of a Test Automation Engineer |
| Implementation and Deployment Strategies | 12% | - Test data management approaches - Test execution strategies and environment management - Configuration management and version control - Integration with CI/CD pipelines |
| Test Automation Architecture | 15% | - Generic Test Automation Architecture (gTAA) - Design principles and patterns for automation - Interoperability and integration concepts - Layered frameworks and separation of concerns |
| Preparing for Test Automation | 14% | - Identifying automation opportunities and constraints - Cost, effort and ROI analysis - Evaluating and selecting test tools - Assessing system testability and architecture |
| Verifying the Test Automation Solution | 12% | - Verifying automation code and infrastructure - Assessing quality and reliability of automation - Validating test suite correctness |
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NEW QUESTION # 35
You have been tasked with adding the execution of build verification tests to the current CI/CD pipeline used in an Agile project. The goal of these tests is to verify the stability of daily builds and ensure that the most recent changes have not altered core functionality. Currently, the first activity performed as part of this pipeline is the static source code analysis. Which of the following stages in the pipeline would you add the execution of these smoke tests to?
Answer: A
Explanation:
Build verification tests (often called smoke tests) are intended to provide fast confirmation that a new build is deployable and that core, end-to-end functionality remains intact. TAE describes these as early, lightweight checks that run after deployment to a suitable test environment, because they need an executable, running instance of the SUT to validate system readiness. Static analysis occurs before packaging/deployment and is a quality activity on source code; smoke tests are runtime checks. Running them before generating the build (A or B) is not feasible because there is no deployed artifact to validate. Running smoke tests as the final activity right before production release (D) defeats their purpose as an early feedback mechanism and increases risk by discovering basic failures too late. The practical and TAE-aligned placement is immediately after deploying the new build into the test environment and before launching broader, longer-running regression, system, or acceptance suites. This ensures failures are detected quickly, prevents wasting time running extensive tests on an unstable build, and provides a clear quality gate for "is this build worth testing further?" Therefore, stage C is the correct insertion point for build verification tests.
NEW QUESTION # 36
Which of the following recommendations can help improve the maintainability of test automation code?
Answer: A
Explanation:
TAE emphasizes that maintainable automation code should be readable, understandable, and easy to modify when the SUT or test intent changes. Deeply nested logic increases cognitive load, makes control flow harder to follow, and complicates debugging and refactoring-especially in automation where synchronization, retries, and error handling are common. Therefore, avoiding excessive nesting is a direct, widely applicable maintainability recommendation. Option A is generally contrary to modern maintainability guidance:
exceptions (used appropriately) typically provide clearer error propagation and richer diagnostic information than manual error codes scattered across call chains. Option C is too broad and misleading: abstraction and patterns are often recommended by TAE to manage complexity and improve maintainability (when applied appropriately); the issue is not "patterns," but misusing them or overengineering. Option D is incorrect because static analysis and developer tooling can substantially improve automation code quality by detecting issues such as dead code, complexity hotspots, duplicated code, insecure practices, and style violations. Thus, the most aligned maintainability recommendation in TAE terms is to avoid overly nested methods.
NEW QUESTION # 37
You are evaluating the best approach to implement automated tests at the UI level for a web app. Specifically, your goal is to allow test analysts to write automated tests in tabular format, within files that encapsulate logical test steps related to how a user interacts with the web UI, along with the corresponding test data. These steps must be expressed using natural language words that represent the actions performed by the user on the web UI. These files will then be interpreted and executed by a test execution tool. Which of the following approaches to test automation is BEST suited to achieve your goal?
Answer: A
Explanation:
The described goal matches the defining characteristics of keyword-driven testing: tests are expressed using keywords (action words) that represent user operations, often arranged in tabular form with parameters/test data. TAE describes keyword-driven approaches as enabling non-programmers (e.g., test analysts) to create and maintain tests by combining high-level keywords such as "Open Browser," "Click," "Enter Text,"
"Select," "Verify Text," etc., while the underlying automation framework maps those keywords to executable code. The use of files interpreted by a test execution tool is also typical: keyword tables (or similar structured specifications) are read and executed by the automation engine. Data-driven testing focuses on separating test logic from test data, typically running the same script multiple times with different datasets; it does not inherently require natural-language action words or tabular step definitions (though it can be combined).
Linear scripting is code-centric and not aligned with analyst-authored natural language step tables. TDD is unrelated to the requirement of tabular, natural-language keyword specification for UI test steps. Therefore, keyword-driven testing is the best fit for the stated approach.
NEW QUESTION # 38
A TAS is used to run on a test environment a suite of automated regression tests, written at the UI level, on different releases of a web app: all executions complete successfully, always providing correct results (i.e., producing neither false positives nor false negatives). The tests, all independent of each other, consist of executable test scripts based on the flow model pattern which has been implemented in a three-layer TAF (test scripts, business logic, core libraries) by expanding the page object model via the facade pattern. Currently the suite takes too long to run, and the test scripts are considered too long in terms of LOC (Lines of Code).
Which of the following recommendations would you provide for improving the TAS (assuming it is possible to perform all of them)?
Answer: D
Explanation:
The primary problem is execution time; correctness and independence are already strong. TAE recommends improving feedback time for long-running regression suites by parallelizing execution when tests are independent and the infrastructure supports it. Because the tests are explicitly independent, they are well- suited to parallel execution across multiple environments (or multiple nodes within an environment), reducing overall wall-clock duration without changing test intent. Option B addresses crash recovery, but the scenario says executions complete successfully; crash recovery does not solve the current bottleneck. Option A changes the modeling pattern; it may or may not reduce LOC, but it introduces risk and rework without directly addressing runtime. Also, flow model and facade-expanded page objects are already architectural choices aimed at maintainability and reuse; replacing them is not the most direct solution for speed. Option D (improving SUT testability) can help in general, but it is invasive, expensive, and not targeted to the stated issue when tests already yield correct results. Therefore, the best improvement is to split the suite and run parts concurrently on different environments to reduce total execution time, consistent with TAE guidance on scaling automation execution.
NEW QUESTION # 39
A CI/CD pipeline consists of two phases: build and deployment. The build phase, among other activities, runs automated test cases at the following test levels: Component Testing (CT) and Component Integration Testing (CIT). If the build phase is successful, the deployment phase is started. The deployment phase first provisions the test environment infrastructure needed to deploy the SUT, then deploys the SUT to this environment, and finally triggers another separate pipeline that runs automated test cases at the following test levels: System Testing (ST) and Acceptance Testing (AT). Which of the following statements is TRUE?
Answer: C
Explanation:
TAE describes quality gates as defined checkpoints in pipelines where objective criteria determine whether the pipeline may proceed (e.g., thresholds, pass/fail rules, coverage, or risk-based acceptance). Automated tests at multiple levels can serve as such gates. In the build phase, CT and CIT are commonly used as strong, fast quality gates because they provide quick feedback on code correctness and integration of closely related components; failures typically block promotion. In the deployment phase, after provisioning and deploying into a test environment, automated System Testing and Acceptance Testing can also serve as quality gates for promoting a build to later stages or release candidates, especially when the organization relies on automated regression and automated acceptance criteria for release decisions. While ST/AT may take longer and may be more prone to environmental factors, TAE still supports using them as gates when they are sufficiently stable, relevant, and aligned with release risk. The scenario explicitly places ST/AT in a separate triggered pipeline, which still qualifies as a gating mechanism if downstream promotion depends on its outcome. Therefore, both CT-CIT and ST-AT can act as quality gates.
NEW QUESTION # 40
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