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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Preparation for Test Automation | 14% | - Assessing suitability for automation - Cost-benefit analysis - Evaluation and selection of tools |
| Topic 2: Continuous Improvement | 19% | - Evolving with technology and processes - Optimization and maintenance - Monitoring and feedback loops |
| Topic 3: Verification of Test Automation Solution | 12% | - Verifying functionality and quality - Reliability and performance checks - Infrastructure validation |
| Topic 4: Test Automation Architecture | 15% | - Frameworks and design patterns - Infrastructure and environment setup - Architecture concepts and layers |
| Topic 5: Implementing Test Automation | 11% | - Development standards and practices - Handling data and interfaces - Testware development and maintenance |
| Topic 6: Reporting and Metrics | 12% | - Metrics for effectiveness and efficiency - Reporting formats and stakeholders - Data collection and analysis |
| Topic 7: Implementation and Deployment Strategies | 12% | - Deployment and execution strategies - Integration with CI/CD pipelines - Pilot projects and rollout |
| Topic 8: Introduction and Objectives for Test Automation | 5% | - Test automation in software development lifecycle - Roles and responsibilities - Purpose and benefits of test automation |
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NEW QUESTION # 68
A new TAS allows the implementation of automated data-driven test scripts. All the tasks planned for the initial deployment of this TAS, aimed at installing and configuring the TAS components and provisioning the infrastructure, will be performed manually by a dedicated, specialized team. This TAS is expected to be deployed in the future in other similar environments. As a TAE, you see a risk that the correct and reproducible deployment of the TAS cannot be guaranteed. Which of the following options is BEST suited for mitigating this risk?
Answer: B
Explanation:
TAE guidance treats repeatable, reliable deployment of the Test Automation Solution as a foundational requirement, especially when the TAS will be rolled out to multiple environments. Manual installation and provisioning are error-prone and difficult to reproduce consistently, even with skilled teams, due to small variations in steps, configuration drift, and undocumented assumptions. The recommended mitigation is to automate deployment activities using repeatable mechanisms (e.g., scripted installation, configuration management, Infrastructure as Code, versioned environment definitions). This supports traceability (what changed and when), repeatability (same inputs produce same environment), and rapid recovery (rebuild environments quickly after failure). Option A is explicitly unsafe because human processes are never guaranteed error-free and do not scale well across environments. Options B and C focus on test data and library organization, which can improve test maintainability, but they do not address the stated risk:
inconsistent and non-reproducible TAS deployment. By automating installation/configuration and infrastructure provisioning, the organization reduces deployment variance and ensures that future deployments of the TAS can be performed reliably, consistently, and auditable across similar environments, aligning directly with TAE best practices for sustaining automation at scale.
NEW QUESTION # 69
(Which of the following statements refers to a typical advantage of test automation?)
Answer: D
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 # 70
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: D
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 # 71
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: B
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 # 72
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 # 73
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