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| Section | Objectives |
|---|---|
| Introduction and Objectives for Test Automation | - Benefits and limitations of test automation - Test automation within different software development lifecycle models - How SUT (System Under Test) architecture impacts test tool suitability |
| Test Automation Reporting and Metrics | - Selecting appropriate metrics (e.g., percent automated, defect detection rate) - Visualizing results for different audiences (technical vs. management) - Proving value to stakeholders - Logging: detailed logs for debugging vs. high-level summaries |
| Continuous Improvement | - Maintaining automated testing assets - Streamlining test suites (removing obsolete tests) - Upgrading tools and libraries - Refactoring test code - Analyzing and adapting the test automation strategy over time |
| Verifying the Test Automation Solution (TAS) | - Automated test suite verification - Checking the test environment setup - Verifying that the automation code itself is correct |
| The Generic Test Automation Architecture (gTAA) | - Tailoring gTAA to create a specific Test Automation Architecture (TAA) - Capabilities in a test automation architecture - Designing a test automation solution - Design principles and design patterns in test automation (Abstraction, Modularity, Separation of data from scripts) - Layering of test automation frameworks (Test Generation, Test Definition, Test Execution, Test Adaptation layers) - Approaches for automating test cases |
| Preparing for Test Automation | - Tool Selection and evaluation for specific technology stacks - Evaluating automation tools and technologies - SUT Testability (Observability and Controllability) - Design for Testability |
| Implementation of Test Automation | - Test data management - Configuration management in test automation - SUT-specific adaptors - Integration of test automation with CI/CD pipelines - Test automation solution (TAS) implementation - Test environment configuration (URLs, Credentials, Test data, Common core library) |
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NEW QUESTION # 71
Which of the following attributes should NOT be included in a test execution report associated with a suite of automated tests?
Answer: B
NEW QUESTION # 72
A release candidate of a SUT, after being fully integrated with all other necessary systems, has successfully passed all required functional tests (90% were automated tests and 10% were manual tests). Now, it is necessary to perform reliability tests aimed at evaluating whether, under certain conditions, that release will be able to guarantee an MTBF (Mean Time Between Failures) in the production environment higher than a certain threshold (expressed in CPU time). Which of the following test environments is BEST suited to perform these reliability tests?
Answer: C
Explanation:
Reliability testing (e.g., long-duration runs, endurance/soak, stability measurements, MTBF assessment) requires an environment that closely resembles production in terms of configuration, resource allocation, deployment topology, integrations, and operational characteristics. TAE guidance emphasizes that measurements like MTBF are highly sensitive to environmental differences such as CPU quotas, background load, database sizing, network topology, virtualization settings, and monitoring agents. A local development environment is unsuitable because it is not representative, is often unstable, and typically lacks full system integration. A build environment focuses on building/packaging and fast verification, not production-like reliability evaluation. An integration environment can validate that systems work together, but it is frequently shared, changes often, and may not match production sizing and operational constraints; it is also commonly disrupted by other teams' deployments. Preproduction (often called staging) is designed to be the closest safe approximation to production while still allowing controlled testing, including reliability and performance- related evaluations, without risking real users or live data. Therefore, preproduction is the best-suited environment to run reliability tests intended to predict production MTBF behavior with credible confidence.
NEW QUESTION # 73
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: B
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 # 74
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: D
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 # 75
Which of the following statement about the implementation of automated regression testing is FALSE?
Answer: B
NEW QUESTION # 76
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