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. FATAL
• C. INFO
• D. WARN

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. 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
• B. Split the generated log file into smaller parts, load them into external files that are loaded into the browser in transparent mode when needed
• C. Use appropriate colors to effectively visually highlight different types of information in the test execution log files
• D. 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

A TAS that performs automated testing in a single test environment was successfully manually installed and configured from a central repository, with all its components in the correct versions. It was also verified that all TAS components in this environment are capable of providing reliable and repeatable performance. The TAS will be used to run several suites of automated regression test scripts on various SUTs in the test environment. Your current goal is to complete all preliminary verifications to ensure that the TAS works correctly. Which of the following activities would you perform FIRST?

• A. Create scripts to automatically install and configure the TAS in the test environment from the central repository
• B. Check whether the TAS connectivity to all required internal systems, external systems, and interfaces is available
• C. Check whether all regression test scripts in a given suite have expected results
• D. Run a given suite multiple times using TAS to determine whether all regression test scripts always provide the same result

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?

• A. Write a single assertion for each property to check whether the data types and formats for that property are as expected in the actual response
• B. Specify the schema for the expected response data (properties, data types, and formats) and validate the actual response data against this schema
• C. Use an artificial intelligence algorithm based on machine learning and image recognition to implement a self-healing capability
• D. Write custom code that parses the actual response data and checks whether the extracted properties, data types, and formats are as expected