2026 Updated Verified CTAL-TAE_V2 Downloadable Printable Exam Dumps The Ultimate ISQI CTAL-TAE_V2 Dumps PDF Review NEW QUESTION # 10 Which of the following layers within the TAA contains technology-specific implementations that enable automated tests to have the execution of their logical actions result in actual interaction with the appropriate interfaces of the SUT? A. Test definition layer B. Test [...]

2026 Updated Verified CTAL-TAE_V2 Downloadable Printable Exam Dumps [Q10-Q26]

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2026 Updated Verified CTAL-TAE_V2 Downloadable Printable Exam Dumps

The Ultimate ISQI CTAL-TAE_V2 Dumps PDF Review

NEW QUESTION # 10
Which of the following layers within the TAA contains technology-specific implementations that enable automated tests to have the execution of their logical actions result in actual interaction with the appropriate interfaces of the SUT?

  • A. Test definition layer
  • B. Test generation layer
  • C. Test execution layer
  • D. Test adaptation layer

Answer: D

Explanation:
TAE describes layered automation architectures where higher layers express intent and test logic, while lower layers handle concrete interaction with specific technologies and interfaces. The test adaptation layer is the layer that "adapts" abstract test actions to the real SUT interaction mechanisms. It typically contains technology-specific adapters, drivers, wrappers, or connectors (e.g., browser drivers, mobile automation bridges, API clients, message-bus connectors, database utilities) that translate logical operations like "click login," "submit order," or "query customer" into the correct low-level calls for the target interface. This is where the details of protocols, locator strategies, synchronization primitives, data access methods, and tool- specific APIs live, shielding higher layers from churn when technologies change. The test execution layer is responsible for orchestrating execution (running suites, scheduling, collecting results, reporting), but not primarily for implementing the technology-specific SUT interaction itself. The test definition layer focuses on how tests are specified (scripts, keywords, models, data), and the test generation layer concerns deriving tests (e.g., model-based generation). Therefore, the layer containing technology-specific implementations enabling actual interaction with SUT interfaces is the test adaptation layer.


NEW QUESTION # 11
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?

  • A. Split the generated log file into smaller parts, load them into external files that are loaded into the browser in transparent mode when needed
  • B. Log the stack trace and amount of memory available to the SUT at the start and end of each test in the suite, in the SUT log files
  • C. Log all expected logging data in the final test execution log file, not only for keywords that fail, but also for keywords that execute successfully
  • D. Use appropriate colors to effectively visually highlight different types of information in the test execution log files

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 # 12
You are currently conducting a Proof of Concept (PoC) aimed at selecting a tool that will be used for the development of a TAS. This TAS will exclusively be used by one team within your organization to implement automated UI-level test scripts for two web apps. The two tools selected for the PoC use JavaScript
/TypeScript to implement the automated test scripts and offer capture and playback capabilities. Three test cases for each of the two web apps were selected to be automated during the PoC. The PoC will compare these two tools in terms of their effectiveness in recognizing and interacting with UI widgets exercised by the test cases, to quickly determine whether test automation is possible and which tool is better. Which of the following TAFs is BEST suited for conducting the PoC?

  • A. A two-layer TAF (test scripts, test libraries)
  • B. A layered TAF with more than three layers
  • C. A one-layer TAF (test scripts)
  • D. A three-layer TAF (test scripts, business logic, core libraries)

Answer: C

Explanation:
For a PoC whose primary goal is rapid feasibility assessment and tool comparison (especially around object recognition and interaction), TAE recommends minimizing framework complexity and upfront engineering.
In a PoC, you want the shortest path to executing representative tests so you can observe tool behavior, stability, locator robustness, synchronization support, and ease of driving the UI widgets in scope. A one-layer approach-simple test scripts with minimal abstraction-reduces the time spent building reusable libraries, enforcing architecture, or creating business layers that are not necessary for answering the PoC question.
Multi-layer frameworks (two-layer and beyond) are more appropriate when you are establishing maintainability, reuse, and scaling for long-term automation. Those benefits matter in the full TAS implementation, but they can distort PoC outcomes by introducing additional design decisions, patterns, and glue code that hide or compensate for tool limitations. Since only six test cases are being automated and the objective is to quickly determine whether UI automation is possible and which tool performs better at widget interaction, the simplest structure (one-layer TAF) is best aligned with TAE PoC guidance: rapid learning, minimal overhead, and clear attribution of outcomes to the tool rather than to framework design.


NEW QUESTION # 13
Which of the following descriptions of what some test automation tools can be used to do is TRUE?

  • A. Autonomously perform exploratory testing sessions based on test charters to find defects within an application
  • B. Analyze test results, code changes, and metrics to predict potential defects and areas of high risk within an application
  • C. Autonomously design intuitive UIs and evaluate them, as well as evaluate the overall UX (User Experience) of an application
  • D. Make video recordings of UI testing sessions to share with stakeholders to show the functionality and appearance of an application

Answer: D

Explanation:
TAE recognizes a range of supporting capabilities offered by test tools beyond pure scripted execution, including reporting, evidence capture, and run artifacts that help stakeholders understand what was tested.
Video recording of UI test sessions is a common feature in several UI automation ecosystems and cloud device
/browser platforms, used to provide visual evidence of steps performed, failures observed, and the application' s look-and-feel during execution. This supports debugging and communication with non-technical stakeholders. Option A overstates what test automation tools do: autonomously designing intuitive UIs and evaluating UX is largely outside typical test automation tool scope and requires human-centered design methods. Option C is also overstated: exploratory testing is inherently human-driven; tools can assist (session notes, heuristics support, telemetry) but do not truly conduct exploratory testing autonomously based on charters in the general TAE framing. Option B touches on advanced analytics and AI/ML-assisted quality insights; while some platforms offer risk prediction features, the phrasing implies broad predictive defect capability, which is not a standard, dependable tool function emphasized in TAE compared with concrete capabilities like artifact capture. Therefore, the clearly true, commonly supported capability is making video recordings of UI testing sessions.


NEW QUESTION # 14
As a TA-E, you have successfully verified that a test automation environment and all other components of the TAS are working as expected. Now your goal is to verify the correct behavior for a given automated test suite that will be run by the TAS. Which of the following should NOT be part of the verifications aimed at achieving your goal?

  • A. Does the level of intrusion of automated test tools influence confidence in the suite's test results?
  • B. Are all automated tests within the suite complete in terms of test data, including expected results?
  • C. Is the connectivity between the TAS and the necessary internal and external systems available and stable?
  • D. Do all automated tests within the suite always provide the same results across multiple runs?

Answer: C

Explanation:
TAE separates two verification scopes: (1) verifying the automation environment and TAS components (infrastructure, connectivity, toolchain readiness), and (2) verifying the correctness and trustworthiness of a specific automated test suite (test completeness, determinism, result validity). The scenario explicitly states that the environment and all TAS components have already been verified as working as expected.
Connectivity between the TAS and internal/external systems is an environment-level readiness check and therefore belongs primarily to the first scope. For the second scope-verifying the behavior of the automated test suite-TAE emphasizes ensuring tests are complete (including correct expected results and data), are repeatable/deterministic across runs, and that the approach/tool intrusion level is understood so stakeholders can interpret confidence in results. That maps to options B, C, and D as suite-focused considerations. Option A repeats an environment connectivity check that should have been addressed in the prior phase and is not a core part of verifying the suite's behavior once environment readiness has been established. Therefore, option A should NOT be part of the suite-behavior verification in this stated situation.


NEW QUESTION # 15
Which of the following recommendations can help improve the maintainability of test automation code?

  • A. Use error codes in test automation code instead of exceptions (if exceptions are supported by the programming language) for error handling
  • B. Avoid using static analyzers on test automation code and other development tools, as they are designed to improve the maintainability of SUT code
  • C. Avoid adopting design patterns that introduce high levels of abstraction in test automation code, such as the flow model pattern
  • D. Avoid producing test automation code containing methods with too many levels of nesting, as deeply nested code is more difficult to understand

Answer: D

Explanation:
TAE emphasizes that maintainable automation code should be readable, understandable, and easy to modify when the SUT or test intent changes. Deeply nested logic increases cognitive load, makes control flow harder to follow, and complicates debugging and refactoring-especially in automation where synchronization, retries, and error handling are common. Therefore, avoiding excessive nesting is a direct, widely applicable maintainability recommendation. Option A is generally contrary to modern maintainability guidance:
exceptions (used appropriately) typically provide clearer error propagation and richer diagnostic information than manual error codes scattered across call chains. Option C is too broad and misleading: abstraction and patterns are often recommended by TAE to manage complexity and improve maintainability (when applied appropriately); the issue is not "patterns," but misusing them or overengineering. Option D is incorrect because static analysis and developer tooling can substantially improve automation code quality by detecting issues such as dead code, complexity hotspots, duplicated code, insecure practices, and style violations. Thus, the most aligned maintainability recommendation in TAE terms is to avoid overly nested methods.


NEW QUESTION # 16
(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?)

  • A. Production environment
  • B. Preproduction environment
  • C. Build environment
  • D. Integration environment

Answer: B

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 # 17
You are evaluating the best approach to implement automated tests at the UI level for a web app. Specifically, your goal is to allow test analysts to write automated tests in tabular format, within files that encapsulate logical test steps related to how a user interacts with the web UI, along with the corresponding test data. These steps must be expressed using natural language words that represent the actions performed by the user on the web UI. These files will then be interpreted and executed by a test execution tool. Which of the following approaches to test automation is BEST suited to achieve your goal?

  • A. Data-driven testing
  • B. Test-driven development
  • C. Linear scripting
  • D. Keyword-driven testing

Answer: D

Explanation:
The described goal matches the defining characteristics of keyword-driven testing: tests are expressed using keywords (action words) that represent user operations, often arranged in tabular form with parameters/test data. TAE describes keyword-driven approaches as enabling non-programmers (e.g., test analysts) to create and maintain tests by combining high-level keywords such as "Open Browser," "Click," "Enter Text,"
"Select," "Verify Text," etc., while the underlying automation framework maps those keywords to executable code. The use of files interpreted by a test execution tool is also typical: keyword tables (or similar structured specifications) are read and executed by the automation engine. Data-driven testing focuses on separating test logic from test data, typically running the same script multiple times with different datasets; it does not inherently require natural-language action words or tabular step definitions (though it can be combined).
Linear scripting is code-centric and not aligned with analyst-authored natural language step tables. TDD is unrelated to the requirement of tabular, natural-language keyword specification for UI test steps. Therefore, keyword-driven testing is the best fit for the stated approach.


NEW QUESTION # 18
An automated test script makes a well-formed request to a REST API in the backend of a web app to add a single item for a product (with ID = 710) to the cart and expects a response confirming that the product is successfully added. The status line of the API response is HTTP/1.1 200 OK, while the response body indicates that the product is out of stock. The API response is correct, the test script fails but completes, and the message to log is: The product with ID = 710 is out of stock. Cart not updated. When this occurs, you are already aware that both the failed test and the API are behaving correctly and that the problem is in the test data. The TAS supports the following test logging levels: FATAL, ERROR, WARN, INFO, DEBUG. Which of the following is the MOST appropriate test logging level to use to log the specified message?

  • A. DEBUG
  • B. WARN
  • C. INFO
  • D. FATAL

Answer: B

Explanation:
TAE logging guidance focuses on making logs actionable while reflecting severity and intent. Here, the test failed due to an expected, non-system fault condition: the product is out of stock, which is a valid business- state response and confirms the API behaved correctly. The issue is that the test data (product availability) did not satisfy the test's precondition. This is not a fatal condition (FATAL) because execution continues and the overall system is not unusable. It is not best treated as ERROR either (not offered as an option here) because an error-level message usually indicates a defect, malfunction, or unexpected failure needing immediate engineering attention. INFO would be too low because it may be lost among normal run messages and does not adequately flag that the test outcome is affected by a precondition violation requiring action (e.g., reseeding data, choosing a different product ID). DEBUG is typically reserved for highly detailed diagnostic traces intended for deeper troubleshooting, not for highlighting a test-data problem affecting test validity.
WARN is intended for abnormal or noteworthy conditions that do not indicate a product defect but may require attention to maintain test reliability. Therefore, WARN is the most appropriate level.


NEW QUESTION # 19
Consider a TAS aimed at implementing and running automated test scripts at the UI level on web apps. The TAS must support cross-browser compatibility for a variety of supported browsers, by ensuring that the same test script will run on such browsers in the same way without making any changes to it. This is achieved by introducing appropriate abstractions into the TAA for connection and interaction with different browsers.
Because of this, the TAS will be able to make direct calls to the supported browsers using each different browser's native support for automation. Which of the following SOLID principles was adopted?

  • A. Open-closed principle
  • B. Dependency inversion principle
  • C. Liskov substitution principle
  • D. Interface segregation principle

Answer: B

Explanation:
The scenario describes introducing abstractions so that test scripts do not depend directly on concrete browser- specific automation implementations. Instead, tests depend on an abstraction (e.g., a "BrowserDriver" interface), while each concrete browser implementation (Chrome, Firefox, Edge, etc.) provides its own adapter using native automation support. This is a classic application of the Dependency Inversion Principle (DIP): high-level modules (test scripts and business-level actions) should not depend on low-level modules (specific browser drivers); both should depend on abstractions. Additionally, details (browser-specific integrations) depend on the abstraction, not the reverse. TAE emphasizes that this reduces coupling and improves maintainability: you can add or update browser implementations with minimal impact on test definitions. While Open-Closed is also supported (extending with new browser adapters without modifying existing tests), the key phrase "introducing appropriate abstractions" specifically to decouple tests from concrete drivers is DIP. Liskov Substitution relates to substituting implementations without breaking correctness, and Interface Segregation concerns keeping interfaces small and specific-neither is as directly targeted by the described architectural decoupling. Therefore, the SOLID principle most clearly adopted is Dependency Inversion.


NEW QUESTION # 20
(Which of the following answers describes the LEAST relevant concern in selecting suitable test automation tools for a test automation project?)

  • A. Has the test team been formed with the different personalities of its members in mind, to ensure that the interaction between them is effective in achieving the objectives of the test automation project?
  • B. What is the degree of technical knowledge and skills within the test team to implement code-based test automation for the project (e.g., in terms of programming and design patterns)?
  • C. In the case of open-source test automation tools, are these tools released under permissive or restrictive licenses, and, if applicable, is it specified whether they can be modified and by whom?
  • D. In the case of commercial test automation tools, what factors determine the licensing costs of these tools (e.g., in terms of the maximum number of users supported and whether the license type is fixed or floating)?

Answer: A

Explanation:
TAE tool selection focuses on factors that materially affect feasibility, total cost of ownership, and long-term sustainability of the Test Automation Solution (TAS): technical fit, skill fit, integration capability, licensing
/legal constraints, and cost model. Option A is directly relevant because the team's capability strongly influences whether a code-heavy tool and framework approach is realistic and maintainable. Option B is relevant because licensing constraints can affect usage rights, redistribution, modification, internal compliance, and legal risk-critical for tool adoption in many organizations. Option D is also highly relevant because commercial licensing costs and licensing models (named user vs. floating, execution limits, parallelism add-ons, feature tiers) impact budgeting and scaling, and therefore the project's viability. Option C, while important for general team effectiveness, is not a primary criterion for selecting automation tools; it does not describe tool capability, integration constraints, cost, or risk in a way that distinguishes one tool from another. TAE typically treats team collaboration/communication and roles as project and organizational concerns (e.g., governance and processes) rather than tool-selection criteria. Therefore, among the provided choices, "team personality mix" is the least relevant concern for choosing suitable test automation tools in a TAE-focused tool selection.


NEW QUESTION # 21
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?

  • A. After deploying the new build to the test environment and before performing more extensive testing
  • B. As a final activity, immediately before releasing the new build into production
  • C. As a first activity, before performing static source code analysis and before generating the new build
  • D. After performing static analysis on the source code and before generating the new build

Answer: A

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 # 22
Which of the following practices can be used to specify the active (i.e., actually available) features for each release of the SUT and determine the corresponding automated tests that must be executed for a given release?

  • A. The use of feature files
  • B. Feature-driven development
  • C. Test-driven development
  • D. The use of feature toggles

Answer: D

Explanation:
TAE materials commonly describe feature toggles (feature flags) as a mechanism to control which features are active in a given release or deployment without necessarily changing the codebase structure for each variant. Because toggles determine what functionality is actually enabled, they provide a practical basis for selecting which automated tests should run for that release configuration. When a feature is disabled via a toggle, executing tests for it can create false failures or wasted effort; when enabled, the corresponding tests become relevant as release evidence. Feature-driven development is a product/development planning approach and does not, by itself, provide an operational mechanism to declare what is active at runtime.
Feature files (often associated with BDD) specify behavior scenarios, but they do not inherently indicate whether a feature is active in a particular release unless explicitly tied to toggles or release configuration.
TDD focuses on coding practices at the unit level and similarly does not specify release-time feature availability. Feature toggles directly express "active vs. inactive" functionality and can be used to drive risk- based and relevance-based test execution decisions, matching the requirement precisely.


NEW QUESTION # 23
Which of the following is the BEST example of how static analysis tools can help improve the test automation code quality in terms of security?

  • A. Static analysis tools can ensure there are no security vulnerabilities within test automation code
  • B. Static analysis tools can help detect the presence of repeated instances of code within test automation code
  • C. Static analysis tools can help detect hard-coded credentials that expose sensitive information within test automation code
  • D. Static analysis tools do not generate false positives when attempting to detect security vulnerabilities within test automation code

Answer: C

Explanation:
TAE highlights that test automation code can introduce security risks, particularly when it handles secrets (API keys, passwords, tokens), test accounts, and connections to production-like systems. Static analysis tools can scan source code for insecure patterns and policy violations without executing the code. A common, high- impact security issue in automation is hard-coded credentials or secrets embedded in scripts, configuration files committed to version control, or test utilities. Detecting these is a direct security-quality improvement: it reduces exposure risk and supports compliance. Option A is incorrect because static analysis can produce false positives; detection heuristics are not perfect. Option B is useful for maintainability (duplication), but it is not specifically a security improvement example. Option D overclaims: static analysis cannot guarantee the absence of security vulnerabilities; it can only detect certain classes of issues. Therefore, the best security- focused example is that static analysis can identify hard-coded credentials and other sensitive data exposure in test automation code.


NEW QUESTION # 24
You have agreed with your organization's managers to conduct a pilot project to introduce test automation.
Managers' expectations about the benefits of automation are too optimistic. Which of the following is LEAST relevant when deciding the scope of the pilot project's objectives?

  • A. Evaluate the performance of an organization's network infrastructure in terms of factors such as availability, bandwidth, latency, packet loss, and jitter
  • B. Evaluate the potential cost savings and benefits (e.g., faster test execution, better test coverage) of using automated testing versus manual testing
  • C. Evaluate the suitability of different test automation tools based on the technology stack used by the applications for which the automated tests will be developed
  • D. Evaluate the knowledge and skills of people who will be involved in automating test cases for applicable test automation frameworks and technologies

Answer: A

Explanation:
TAE positions pilot projects as a controlled way to validate feasibility, calibrate expectations, and reduce adoption risk. Pilot objectives typically include assessing tool fit (technical compatibility, integration, reporting, maintainability), estimating realistic benefits and costs (execution speed, regression efficiency, coverage improvements, maintenance overhead), and assessing team readiness (skills, training needs, required roles). Those align directly with options A, B, and C. Network performance characteristics can matter for distributed test execution or remote environments, but evaluating enterprise network infrastructure at a deep level (availability, jitter, packet loss) is generally not a primary objective for a test automation pilot- especially when the central concern is overly optimistic expectations about automation benefits. A pilot should focus on demonstrating what can be automated, at what cost, with what stability and maintainability, and what process changes are needed. Infrastructure constraints may be observed as risks during the pilot, but a full network performance evaluation is more characteristic of IT operations or performance engineering initiatives, not a test automation introduction pilot scope. Therefore, option D is the least relevant when defining the pilot's objectives in a TAE-aligned approach.


NEW QUESTION # 25
In a first possible implementation, the automated test scripts within a suite locate and interact with elements of a web UI indirectly through the browsers using browser-specific drivers and APIs, provided by an automated test tool used as part of the TAS. In an alternative implementation, these test scripts locate and interact with elements of the same web UI directly at the HTML level by accessing the DOM (Document Object Model) and internal JavaScript code. The first possible implementation:

  • A. Has a lower level of intrusion than the alternative implementation, and therefore its test scripts are less likely to produce false positives
  • B. Has a lower level of intrusion than the alternative implementation, and therefore its test scripts are more likely to produce false positives
  • C. Has a higher level of intrusion than the alternative implementation, and therefore its test scripts are less likely to produce false positives
  • D. Has the same level of intrusion as the alternative implementation, and therefore the risk of test scripts producing false positives is the same in both cases

Answer: A

Explanation:
TAE describes "intrusiveness" as the degree to which automation reaches into internal implementation details of the SUT rather than interacting through externally visible, user-realistic interfaces. Using browser drivers and browser automation APIs exercises the UI similarly to a real user (via the browser's supported automation hooks), which is generally less intrusive than directly manipulating the DOM and internal JavaScript. Direct DOM/JS access can bypass real user interaction pathways, skip browser event chains, and depend on internal structures that are not part of the stable external contract. This increases the risk of false positives: tests may
"pass" by forcing UI states or reading internal values even when the application would not behave correctly for real users. Less intrusive automation (through browser-level drivers) tends to provide higher confidence that observed behavior reflects real user experience, reducing the chance that tests succeed while user-visible behavior is broken. TAE therefore associates lower intrusion with stronger validity of results and lower false- positive risk, especially for system/UI-level validation. While browser-driven automation can still be flaky for other reasons (timing, environment), in the specific comparison of interaction method, browser-driver-based execution is the less intrusive option and is less likely to create false positives than direct internal DOM/JS manipulation.


NEW QUESTION # 26
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