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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Test Automation Validation | 15% | - Root Cause Analysis - Test Automation Assessment Metrics - Test Automation Verification |
| Topic 2: Introduction and Objectives for Test Automation | 5% | - Success Factors for Test Automation - Purpose of Test Automation - Risks and Benefits of Test Automation |
| Topic 3: Preparation for Test Automation | 15% | - Test Automation Architecture Design - Design for Testability and Automation - SUT Analysis for Test Automation - Rollout and Deployment Considerations - Test Automation Tool Evaluation and Selection |
| Topic 4: Transitioning from Manual to Automated Testing | 15% | - Maintaining Automation Consistency - Automation Migration Strategies - Criteria for Manual vs. Automated Testing |
| Topic 5: Test Automation Strategy and Roadmap | 15% | - Test Automation Planning - Test Automation Maintenance - Test Automation Governance - Test Automation Integration with CI/CD |
| Topic 6: Execution and Implementation of Test Automation | 35% | - Logging and Reporting Strategies - Implementing Test Automation Solutions - Designing Test Automation Solutions - Verifying Test Automation Solutions - Building Robust Automated Test Suites - Developing Test Automation Solutions |
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NEW QUESTION # 61
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 # 62
Which of the following information in API documentation is LEAST relevant for implementing automated tests on that API?
Answer: A
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 # 63
The last few runs for a suite of automated keyword-driven tests on a SUT were never completed. The test where the run was aborted was not the same between runs. Currently, it is not possible to identify the root cause of these aborts, but only determine that test execution aborted when exceptions (e.g., NullPointerException, OutOfMemoryError) occurred on the SUT by analyzing its log files. Test execution log files are currently generated, in HTML format, by the TAS as follows: all expected logging data is logged for each keyword in intermediate log files. This data is then inserted into the final log file only for keywords that fail, while only a configurable subset of that data is logged for keywords that execute successfully. Which of the following actions (assuming it is possible to perform all of them) would you take FIRST to help find the root cause of the aborts?
Answer: C
Explanation:
TAE stresses that when diagnosing intermittent aborts with unclear root cause, the first priority is ensuring sufficient, consistent observability from the automation side to reconstruct what happened immediately before termination. In this scenario, the suite aborts in different tests across runs, and the final HTML report currently contains full detail only for failing keywords, while successful keywords have reduced logging. If the run aborts due to an exception in the SUT, the "last executed successful keywords" and their full context may be essential to correlate actions with the SUT failure point. The fastest, most direct improvement is to include complete keyword-level logging for successful steps as well, at least until the issue is understood.
This aligns with TAE guidance to temporarily increase logging verbosity during investigation to capture the sequence of actions, inputs, timings, and states leading up to failure. Option A could be helpful, but it changes SUT-side logging and may require additional access or instrumentation; also, it does not guarantee visibility into the exact automation step sequence. Options B and D improve presentation/performance of logs but do not add diagnostic content. Therefore, first increase the completeness of the final execution logs for all keywords to maximize evidence for root cause analysis.
NEW QUESTION # 64
What would be a goal of test automation in a local development environment?
Answer: B
Explanation:
The local development environment is where software is initially created and individual components can be tested through automation to verify their functional suitability. CTAL-TAE states that automated component testing, GUI testing, and API testing may all occur in this environment. Developers can also use an integrated development environment to perform white-box testing and identify coding and quality problems as early as possible. Checking the correctness of a complete build is principally associated with the build environment.
Verification of interaction with other systems belongs to an integration or system integration environment once the relevant components have been combined. Performance-efficiency assessment is particularly associated with preproduction because that environment should resemble production closely. Therefore, verifying component functionality most accurately represents a typical test automation objective in a local development environment.
(https://www.istqb.org/wp-content/uploads/2024/11/ISTQB_CTAL-TAE_Syllabus_v2.0.pdf)
NEW QUESTION # 65
Which of the following statements about contract testing is TRUE?
Answer: C
Explanation:
TAE describes contract testing as verifying that two parties (e.g., consumer and provider services) adhere to an agreed interface contract, enabling earlier, more targeted detection of integration mismatches without requiring full end-to-end integration in every test run. A key distinction in approaches is indeed who defines
/publishes the contract. In provider-driven contracts, the provider defines the contract describing what it offers; consumers validate compatibility against it. In consumer-driven contract testing, consumers define expectations (often per consumer), and providers verify they satisfy those expectations. Option A is false because stubs/mocks (or simulated counterparts) are frequently used to allow each side to test independently and deterministically, which is one of contract testing's practical strengths. Option B is too narrow: contract testing can apply beyond REST (e.g., GraphQL, gRPC, messaging/event contracts). Option D is also too restrictive: it can apply to asynchronous interactions (events/messages) as well as synchronous calls.
Therefore, the accurate statement is option C.
NEW QUESTION # 66
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