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| Section | Objectives |
|---|---|
| Test Automation Architecture | - Test automation frameworks - Maintainability and scalability considerations - Design principles for automation architecture |
| Integration and Deployment (CI/CD) | - Integration into CI/CD pipelines - Toolchain integration - Execution strategies in continuous testing |
| Test Automation Maintenance and Evolution | - Maintaining automated test assets - Refactoring automation solutions - Handling application changes |
| Test Automation Reporting and Metrics | - Key metrics for test automation effectiveness - Automation reporting approaches |
| Transition and Deployment | - Scaling test automation adoption - Introducing automation into organizations |
| Preparing for Test Automation | - Risk analysis for automation scope - Selecting test cases for automation - Feasibility assessment for automation |
| Test Automation Solution Development | - Implementation of automated test solutions - Handling test environments - Test data management |
| Introduction to Test Automation Engineering | - Test automation within the software lifecycle - Goals and value of test automation - Success factors for test automation |
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NEW QUESTION # 13
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 # 14
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 # 15
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: D
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 # 16
Automated tests run by a TAS on a SUT can be subject to sudden bursts of messages to log during their execution. All log messages that occur during execution must be permanently stored in the corresponding test execution logs by the TAS for later analysis. If logging is not performed correctly, these bursts can reduce the execution speed of these automated tests, causing them to produce unreliable results. Which of the following solutions would you expect to be MOST useful to address this issue for TAS logging?
Answer: D
Explanation:
TAE highlights that logging must balance diagnostic value with execution performance and reliability. Direct synchronous file I/O for every log message can become a bottleneck during bursts, increasing latency and perturbing the timing of the automated interactions-especially for UI or time-sensitive integration tests- leading to flaky outcomes. Since all messages must be permanently stored, dropping burst logs (option C) violates the requirement. NTP synchronization (option A) helps correlate events across systems, but it does not address the performance overhead caused by bursty logging. The most useful approach is to buffer log events in memory and flush them periodically or asynchronously to disk. A circular buffer (or similar in- memory queue) reduces immediate I/O pressure and smooths bursts, while still preserving messages for later analysis when combined with an appropriate flush strategy and sizing. This design is aligned with TAE's emphasis on making the TAS itself reliable and non-intrusive, ensuring logging supports triage without materially slowing or destabilizing test execution. Therefore, buffering in memory and periodically flushing to log files is the best solution.
NEW QUESTION # 17
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: A
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 # 18
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