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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Test Automation Architecture | 15% | - Generic Test Automation Architecture (gTAA) - Interoperability and integration concepts - Design principles and patterns for automation - Layered frameworks and separation of concerns |
| Topic 2: Introduction and Objectives for Test Automation | 5% | - Test automation in software development lifecycle models - Purpose, benefits and limitations of test automation - Roles and responsibilities of a Test Automation Engineer |
| Topic 3: Reporting and Metrics | 12% | - Defining relevant automation metrics - Collecting and analyzing data - Reporting to stakeholders - Visualization and dashboards |
| Topic 4: Verifying the Test Automation Solution | 12% | - Validating test suite correctness - Verifying automation code and infrastructure - Assessing quality and reliability of automation |
| Topic 5: Continuous Improvement | 19% | - Refactoring and optimizing automation - Upgrading tools and frameworks - Adapting to new technologies and requirements - Streamlining and maintaining test assets |
| Topic 6: Implementing Test Automation | 11% | - Managing technical debt - Handling synchronization, stability and reliability - Planning and running pilot projects - Developing and maintaining automation components |
| Topic 7: Implementation and Deployment Strategies | 12% | - Test data management approaches - Test execution strategies and environment management - Integration with CI/CD pipelines - Configuration management and version control |
| Topic 8: Preparing for Test Automation | 14% | - Assessing system testability and architecture - Identifying automation opportunities and constraints - Evaluating and selecting test tools - Cost, effort and ROI analysis |
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NEW QUESTION # 29
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 # 30
An API's response to a request made to the corresponding endpoint should return some specific data about a payment transaction in JSON format. In particular, your goal is to write the test automation code, keeping it as short as possible, aimed at determining whether that response includes certain properties (transaction_id, amount, status, timestamp) with the data types and formats expected. Assuming that the TAF provides all the necessary support to validate the specified API response, how would you BEST achieve your goal?
Answer: B
Explanation:
TAE encourages using the highest-leverage validation mechanisms available in the framework/tooling to keep tests concise, expressive, and maintainable. When validating JSON responses for presence of fields plus correct data types and formats, schema-based validation (e.g., JSON Schema or an equivalent contract/schema mechanism provided by the TAF) is typically the most efficient approach. It allows you to declare the expected structure once (required properties, types, constraints such as regex/date-time format, numeric ranges) and then validate the whole response in a single operation. This minimizes code and reduces repetitive assertions while producing clearer diagnostics when validation fails. Option B can work but usually results in more lines of code and repeated checks, and it is easier to miss constraints (e.g., timestamp format). Option D increases code volume and duplication by re-implementing parsing and validation logic that the TAF already provides, increasing maintenance burden. Option C is irrelevant to the goal of validating response properties
/types/formats. Therefore, specifying an expected schema and validating the response against it is the best way to keep code short and aligned with TAE maintainability recommendations.
NEW QUESTION # 31
Consider a TAS implemented to perform automated testing on native mobile apps at the UI level, where the TAF implements a client-server architecture. The client runs on-premise and allows creation of automated test scripts using TAF libraries to recognize and interact with the app's UI objects. The server runs in the cloud as part of a PaaS service, receiving commands from the client, translating them into actions for the mobile device, and sending the results to the client. The cloud platform hosts several mobile devices dedicated for use by this TAS. The device on which to run test scripts/test suites is specified at run time. You are currently verifying whether the test automation environment and all other TAS/TAF components work correctly. Which of the following activities would you perform to achieve your goal?
Answer: A
Explanation:
The task is to verify the test automation environment and TAS/TAF components, not to validate the correctness of specific test suites. In a client-server TAF for mobile automation, a critical component is the automation library layer that exposes functions to locate and interact with UI objects, and that communicates with the cloud server/device farm. TAE guidance highlights that environment verification should focus on ensuring that the automation tooling stack can reliably perform its fundamental operations: connect to the execution infrastructure, select target devices at runtime, execute commands, and receive results. Checking that the TAF libraries correctly recognize and interact with widgets directly validates that the end-to-end automation mechanism (client # server # device # response) is functioning. Option A is not appropriate because the server is on PaaS; infrastructure management is typically handled by the provider and is not part of validating your TAS operation. Option B is incorrect because the scenario states the device is specified at run time, so hard-coding device references is not the expected design and is not the right verification focus.
Option D concerns test suite correctness (expected results), which is a later step after confirming the automation environment works. Therefore, verifying that the TAF libraries function as expected is the correct activity.
NEW QUESTION # 32
Which of the following statements about the relationship between TAA, TAS and TAF is true?
Answer: A
Explanation:
In TAE terminology, the Test Automation Architecture (TAA) is the conceptual, high-level blueprint that describes how automation will be structured, what layers exist, how components interact, and how the automation connects to the SUT and supporting systems. The Test Automation Solution (TAS) is the concrete realization of that architecture in a specific context-tools, infrastructure, pipelines, conventions, and components assembled to deliver automated testing capability. The Test Automation Framework (TAF) is a structured set of reusable libraries, guidelines, and mechanisms that supports efficient development, execution, reporting, and maintenance of automated tests; it is commonly a key part used to build the TAS.
TAE documents commonly present this relationship as: TAA (design) # implemented as TAS (solution) # constructed using one or more TAFs (framework elements) plus tools and environment components. Options B, C, and D invert these relationships and misrepresent the concept that architecture is implemented by a solution, not the other way around. Therefore, the statement that a TAF can be used to implement a TAS, which is an implementation of a TAA, is the correct relationship.
NEW QUESTION # 33
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?
Answer: B
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 # 34
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