ISTQB CT-TAE - Certified Tester Test Automation Engineer

The best recommendation for improving the Test Automation System (TAS) in this scenario is to implement standard setup and teardown functions at the test case level. This approach promotes reusability and efficiency by allowing the same initial and final sequences of steps to be used across multiple test cases. By centralizing these sequences into common functions, any changes to the setup or teardown process only need to be made in one place, thus reducing maintenance efforts and potential for errors. Furthermore, it streamlines the execution of test cases and makes the automation framework more robust and easier to manage.

References = This recommendation aligns with the ISTQB Test Automation Engineer guidelines, which advocate for the use of reusable components and functions to enhance the maintainability and scalability of the test automation architecture12. The principles of designing an effective TAS include creating modular and reusable components that can be shared across different test cases, which is essential for improving the overall efficiency and reliability of the test automation efforts12.

 The goal is to verify the completeness, consistency, and correct behavior of an automated test suite (TAS) that has been successfully installed in the System Under Test (SUT) environment. Since the TAS has already been proven to install successfully, checking the repeatability of the TAS loading in the SUT environment (option C) is not a relevant check for this goal. The focus should be on verifying the correctness of the test cases and their outcomes. This includes ensuring that all test cases contain the expected results (option A), verifying that the postconditions have been fulfilled for all test cases (option B), and checking that all test cases produce repeatable outcomes (option D).

References = This explanation is based on the ISTQB’s guidelines for verifying the technical aspects of a deployed test automation solution and ensuring the correct behavior of test scripts and suites1.

For the scenario of automating functional tests at the system test level via the Command Line Interface (CLI) of the SUT, with the requirements for fast and cheap maintenance, low cost for adding new tests, and high independence from the automation tool, the most suitable scripting technique is Data-driven scripting. This approach externalizes test data from the scripts into separate data files or repositories, allowing for the reuse of test scripts with different sets of data. Data-driven scripting is ideal for meeting the specified requirements because it enables rapid execution of a large number of test cases by merely changing the input data, without the need to alter the scripts themselves. This significantly reduces maintenance costs and the effort required to add new tests, as the core script remains the same. Moreover, this technique enhances the independence of the automated tests from the specific tools used, as the focus is on the data and the generic actions performed by the scripts, making it the most suitable choice for the described needs.

The best approach for collecting metrics that measure code coverage is to automate the process as much as possible. Option C suggests an automated solution where the testware records the code coverage for each run and exports the data to an Excel spreadsheet. This spreadsheet is pre-formatted to update a trend analysis bar chart automatically. This method not only minimizes manual overheads and errors but also provides stakeholders with an easy-to-understand visual representation of the coverage trends over time. It ensures that the scope of the regression test pack is continuously reflecting the enhancements made to the SUT, with coverage metrics that should not drop and ideally increase, aligning with the requirements for trend-based metrics.

References = The ISTQB Test Automation Engineer syllabus and industry best practices recommend the use of automated solutions for tracking and analyzing test metrics. This includes the automation of metric collection and the use of trend analysis to monitor the effectiveness of the test suite over time123.