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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Execution and Implementation of Test Automation | 35% | - Designing Test Automation Solutions - Implementing Test Automation Solutions - Developing Test Automation Solutions - Verifying Test Automation Solutions - Logging and Reporting Strategies - Building Robust Automated Test Suites |
| Topic 2: Test Automation Validation | 15% | - Root Cause Analysis - Test Automation Verification - Test Automation Assessment Metrics |
| 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% | - Purpose of Test Automation - Success Factors for Test Automation - Risks and Benefits of Test Automation |
| Topic 5: Test Automation Strategy and Roadmap | 15% | - Test Automation Integration with CI/CD - Test Automation Governance - Test Automation Maintenance - Test Automation Planning |
| Topic 6: Preparation for Test Automation | 15% | - Test Automation Architecture Design - Rollout and Deployment Considerations - Design for Testability and Automation - SUT Analysis for Test Automation - Test Automation Tool Evaluation and Selection |
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NEW QUESTION # 23
(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 # 24
Which factor will support maintainability of test automation solutions?
Answer: B
Explanation:
The CTAL-TAE syllabus identifies common naming conventions as an important clean-code practice supporting Test Automation Solution maintainability. Classes, methods, variables, and other automation elements should use meaningful and consistent names so that TAEs can quickly understand their purpose and locate the components that require modification. Consistent names therefore reduce comprehension effort and make maintenance more efficient across a team. Hardcoded parameter values have the opposite effect because values that change frequently may need modification in many different locations; the syllabus explicitly recommends avoiding hardcoding where possible. Test-driven development is primarily a software- development approach rather than a general maintainability factor for an existing automation solution.
Keyword-driven testing may improve abstraction in appropriate contexts, but it also introduces implementation and maintenance complexity. Therefore, common naming conventions are the directly supported maintainability factor.
(https://istqb.org/wp-content/uploads/2024/11/ISTQB_CTAL-TAE_Syllabus_v2.0.pdf?utm_source=chatgpt.
com)
NEW QUESTION # 25
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: C
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 # 26
You are a TAE responsible for a TAS that is used on several products, all of which have complex UIs. A substantial proportion of the automated tests break on a regular basis, usually for reasons associated with the UI. The investigation and maintenance this requires is significantly reducing the productivity of the teams and the return on investment.
You are looking for ways to improve the test cases in this TAS. Which of the following approaches would be MOST appropriate?
a) Artificial intelligence
b) Test histograms
c) Reliability growth modelling
d) Schema validation
e) Operational profiles
Answer: C
Explanation:
Both artificial intelligence and test histograms directly address unstable UI automation. CTAL-TAE explains that test histograms visualize test-result and test-data trends and help TAEs identify fragile test cases that should be refactored or redesigned. This is particularly useful when a substantial proportion of tests repeatedly break. AI and machine-learning techniques provide an additional UI-specific improvement: tools can detect changed locator values, identify replacement selectors through ML or image-recognition techniques, and apply self-healing mechanisms that reduce locator-related maintenance. Schema validation is primarily applicable to API and database data structures rather than complex UI instability. Reliability growth modelling and operational profiles address software reliability concerns rather than recurring automated UI maintenance. Therefore, combining test histograms for identifying fragile tests with AI-based self-healing for UI locator changes gives the strongest solution.
(https://www.istqb.org/wp-content/uploads/2024/11/ISTQB_CTAL-TAE_Syllabus_v2.0.pdf)
NEW QUESTION # 27
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: A
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 # 28
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