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| Section | Objectives |
|---|---|
| Test Automation Solution Development | - Implementation of automated test solutions - Test data management - Handling test environments |
| Test Automation Architecture | - Test automation frameworks - Design principles for automation architecture - Maintainability and scalability considerations |
| Test Automation Reporting and Metrics | - Automation reporting approaches - Key metrics for test automation effectiveness |
| Test Automation Maintenance and Evolution | - Maintaining automated test assets - Refactoring automation solutions - Handling application changes |
| Preparing for Test Automation | - Feasibility assessment for automation - Selecting test cases for automation - Risk analysis for automation scope |
| Transition and Deployment | - Scaling test automation adoption - Introducing automation into organizations |
| Integration and Deployment (CI/CD) | - Execution strategies in continuous testing - Integration into CI/CD pipelines - Toolchain integration |
| Introduction to Test Automation Engineering | - Goals and value of test automation - Success factors for test automation - Test automation within the software lifecycle |
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NEW QUESTION # 38
(Which of the following statements about how test automation is applied across different software development lifecycle models is TRUE?)
Answer: B
Explanation:
TAE guidance emphasizes that Agile/iterative delivery drives frequent change and frequent regression risk, which often leads teams to expand automated regression suites over time. As suites grow, they can become slower, costlier to maintain, and harder to keep stable-especially if the suite is concentrated too heavily at the UI level. For this reason, TAE stresses investing in automation across multiple test levels (unit
/component, API/service, and selected UI), aligning with principles behind balanced automation strategies (often illustrated by the "test pyramid"). This directly supports option A. Option B is not generally true: in Waterfall/V-model, testing activities (including automation design and implementation) are planned and may start early, but execution and refinement occur across phases aligned with integration and system readiness- not "usually only during the last phase." Option C is too absolute: the test pyramid is a common heuristic, but TAE does not mandate it "regardless of context"; constraints like legacy systems, risk, architecture, and tooling can change the optimal distribution. Option D is incorrect because unit testing is typically a developer responsibility in both Agile and V-model contexts; testers may support, review, or contribute but do not
"write automated unit tests" as a defining V-model rule. Therefore, A best matches documented lifecycle realities and maintenance concerns.
NEW QUESTION # 39
Automated tests at the UI level for a web app adopt an asynchronous waiting mechanism that allows them to synchronize test steps with the app, so that they are executed correctly and at the right time, only when the app is ready and has processed the previous step: this is done when there are no timeouts or pending asynchronous requests. In this way, the tests automatically synchronize with the app's web pages. The same initialization tasks to set test preconditions are implemented as test steps for all tests. Regarding the pre- processing (Setup) features defined at the test suite level, the TAS provides both a Suite Setup (which runs exactly once when the suite starts) and a Test Setup (which runs at the start of each test case in the suite).
Which of the following recommendations would you provide for improving the TAS (assuming it is possible to perform all of them)?
Answer: B
Explanation:
TAE strongly discourages replacing robust, app-aware synchronization with manual waits. Automatic synchronization based on application readiness signals (e.g., no pending async requests) reduces flakiness and unnecessary delays. Hard-coded waits (A) are brittle and slow; polling waits (C) can be better than fixed sleeps but are still generally inferior to event/readiness-based synchronization already in place. The improvement opportunity described is that the same initialization steps are repeated in every test as explicit test steps, which increases test script length, duplication, and maintenance effort. TAE recommends centralizing common setup logic using framework setup/teardown mechanisms to enforce consistency and reduce duplication. Since the initialization tasks are needed to set preconditions for each test (so each test starts from a known state and remains independent), they belong in the Test Setup, which runs before each test case. Putting them in Suite Setup (D) would run them only once, risking that later tests inherit polluted state, making tests interdependent and more brittle. Therefore, moving shared per-test initialization tasks into the Test Setup is the best recommendation.
NEW QUESTION # 40
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: A
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 # 41
Which of the following statements about a test progress report produced for an automated test suite is TRUE?
Answer: A
Explanation:
TAE reporting guidance emphasizes that stakeholders must be able to interpret results in context. A fundamental contextual attribute is the test environment: where the SUT was deployed, what configuration was used, and (by implication) what data and integrations were in play. Without environment identification, results can be misleading, non-reproducible, or not comparable across runs (e.g., failures caused by environment instability vs. product defects). Therefore, including the environment in the progress report is a core requirement. Option B is incorrect because TAE explicitly promotes tailoring reports to stakeholder needs; different audiences require different levels of detail, summaries, and views. Option A is generally too granular for a progress report: step-level timestamps belong more to detailed execution logs and troubleshooting artifacts, not to a progress report intended to communicate status efficiently. Option D may be included in some reports, but it is not as universally required as the environment identifier; and in TAE,
"progress report" tends to focus on overall status (what ran, what passed/failed, trends, coverage, environment) rather than per-test timing metadata. Thus, the reliably true statement is that the report should indicate the test environment.
NEW QUESTION # 42
(In User Acceptance Testing (UAT) for a new SUT, in addition to the manual tests performed by the end- users, automated tests are performed that focus on the execution of repetitive and routine test scenarios. In which of the following environments are all these tests typically performed?)
Answer: A
Explanation:
TAE distinguishes test environments by purpose and risk. User Acceptance Testing is typically performed in an environment that is as production-like as feasible (configuration, data shape, integrations) but still controlled and safe for testing activities. This is commonly referred to as preproduction (often "staging"): it supports realistic end-to-end flows, allows business users to validate that the SUT meets acceptance criteria, and enables running routine/repetitive automated checks without risking live operations. A build environment is focused on compiling/packaging and basic verification, not business acceptance. An integration environment is used to validate interactions among components/systems, but may not reflect full production- like configuration, and it's often shared and volatile-less suitable for formal acceptance activities involving end users. Production is generally avoided for UAT because acceptance testing can alter live data, disrupt users, and introduce unacceptable business risk; production testing is typically limited to tightly controlled smoke checks, monitoring, or specific "in-production" validation patterns with strong safeguards. Therefore, the environment in which both end-user manual UAT and supporting automated routine scenarios are typically executed is the preproduction environment, aligning with TAE's guidance on balancing realism with risk containment.
NEW QUESTION # 43
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