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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Preparing for Test Automation | 14% | - Evaluating and selecting test tools - Identifying automation opportunities and constraints - Assessing system testability and architecture - Cost, effort and ROI analysis |
| Topic 2: Implementing Test Automation | 11% | - Planning and running pilot projects - Handling synchronization, stability and reliability - Managing technical debt - Developing and maintaining automation components |
| Topic 3: Implementation and Deployment Strategies | 12% | - Configuration management and version control - Test data management approaches - Integration with CI/CD pipelines - Test execution strategies and environment management |
| Topic 4: Continuous Improvement | 19% | - Adapting to new technologies and requirements - Refactoring and optimizing automation - Upgrading tools and frameworks - Streamlining and maintaining test assets |
| Topic 5: Verifying the Test Automation Solution | 12% | - Assessing quality and reliability of automation - Validating test suite correctness - Verifying automation code and infrastructure |
| Topic 6: Test Automation Architecture | 15% | - Generic Test Automation Architecture (gTAA) - Layered frameworks and separation of concerns - Interoperability and integration concepts - Design principles and patterns for automation |
| Topic 7: Introduction and Objectives for Test Automation | 5% | - Roles and responsibilities of a Test Automation Engineer - Purpose, benefits and limitations of test automation - Test automation in software development lifecycle models |
| Topic 8: Reporting and Metrics | 12% | - Reporting to stakeholders - Visualization and dashboards - Collecting and analyzing data - Defining relevant automation metrics |
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NEW QUESTION # 28
You are working for a clothing retailer that has big stores in many cities. Your TAS, for the first time, has just been used for reliability and stress testing of the overnight batch processing that collects sales transactions from the stores and adds them to a data warehouse; functional suitability tests have been reused for these runs.
All tests have finished normally but their results have not been satisfactory, and it has been difficult to understand the nature of the defect or defects that have been causing the failures.
What data, if added to the test logs, would MOST likely help with debugging in this situation?
a) Dynamic data about the status of the test platforms
b) Screenshots taken during test execution
c) Crash dumps and stack traces
d) Values of randomly generated test input data
e) Counts of the quantity of test cases executed during each run
Answer: D
Explanation:
For reliability and stress testing, CTAL-TAE specifically recommends capturing dynamic information about the SUT and recording execution counters. Dynamic platform information can expose conditions such as resource utilization, memory leaks, or other runtime degradation that may explain failures occurring during intensive overnight processing. The syllabus also states that when reliability or stress testing involves numerous test cycles, a counter should be logged so investigators can determine how many times the test cases were executed and correlate failures with prolonged execution. Crash dumps and stack traces are particularly relevant when the SUT crashes, but the scenario explicitly states that the tests finished normally.
Random input values are important only when randomized testing is used, which is not stated. Screenshots provide little diagnostic value for backend overnight batch reliability testing. Therefore, a and e are the most useful data.
(https://www.istqb.org/wp-content/uploads/2024/11/ISTQB_CTAL-TAE_Syllabus_v2.0.pdf)
NEW QUESTION # 29
Which of the following should be done when checking the composition of the test suite?
Answer: A
Explanation:
ISTQB distinguishes several verification activities for an automated test suite: checking its composition, verifying tests that use new TAF features, considering repeatability, and examining tool intrusiveness. When specifically checking test-suite composition, the syllabus requires checking completeness and confirming that the correct versions of the TAF and SUT are being used. This prevents a suite from being executed against incompatible framework or application versions and helps ensure that its expected results and test data remain valid. Option A belongs to the separate activity of verifying new TAF features. Option B concerns the separate assessment of automation-tool intrusiveness. Option D describes repeatability, where repeated execution should produce reliable and consistent results. Since the question asks specifically about composition, validating the correct TAF and SUT versions is the precise syllabus-defined action.
(https://www.istqb.org/wp-content/uploads/2024/11/ISTQB_CTAL-TAE_Syllabus_v2.0.pdf)
NEW QUESTION # 30
When choosing an automation tool, which would be the BEST option for automation testers who have programming skills?
Answer: D
NEW QUESTION # 31
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: A
NEW QUESTION # 32
An automated test case that should always pass sometimes passes and sometimes fails intermittently (non- deterministic behavior) when executed in the same test environment, even if no code (i.e., SUT code or the test automation code) has been changed. Which of the following statements about the root cause of this non- deterministic behavior is TRUE?
Answer: B
Explanation:
TAE treats non-deterministic (flaky) test behavior as a symptom that can originate from multiple sources:
timing and synchronization issues, race conditions, concurrency, environmental variability (resource contention, network latency), unstable test data, third-party dependencies, or hidden state leakage between tests. Because these causes often span boundaries-application code, infrastructure, deployment configuration, test tooling, and data pipelines-finding the true root cause frequently requires collaboration beyond the TAE role. Developers may need to inspect application logs, thread behavior, and recent architectural assumptions; system engineers may need to analyze resource saturation, container orchestration events, network anomalies, or environment drift. Option A is too specific and assertive: the root cause is not necessarily a race condition, and logs may not be sufficient to identify it. Option C is incorrect because no code change does not imply the environment is the only cause; flaky behavior can stem from hidden nondeterminism in the system or tests that is always present but only sometimes triggers. Option D is also incorrect; intermittent failures are often harder to diagnose than consistent deterministic failures because evidence is less reproducible. Therefore, the true statement is that determining the root cause may require support from developers and system engineers in addition to the TAE.
NEW QUESTION # 33
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