Free ISTQB CTAL-TTA Practice Exam with Questions & Answers | Set: 2

The purpose of an HTML checker is to verify compliance with standards. This tool ensures that the HTML code of a web application adheres to the defined web standards, which is crucial for cross-browser compatibility, proper rendering, and avoiding common coding errors​​.

The common name for the automated testing technique that separates test input data and expected results from the control script is Keyword-driven testing. In this approach, test scripts are written using keywords related to the application under test, which are easy to read and can be interpreted by a script engine to perform testing actions.

Explanation: This methodology allows for the reusability of scripts and easier maintenance because the test data and the scripts that use the data are maintained separately.

In the context of software testing, different safety integrity levels (SIL) require different levels of rigor in testing. According to the IEC61508 standard, for software components rated at SIL 2, achieving 100% statement coverage and 100% decision coverage is recommended. Statement coverage ensures that every line of code is executed at least once during testing, while decision coverage ensures that every decision in the code (e.g., every branch of an IF statement) is executed on both the true and false sides. These coverage criteria ensure a thorough testing of the software components to validate that they behave correctly in all circumstances. Multiple condition coverage and MC/DC coverage (Options A and B) are more rigorous and typically required for higher SIL levels, such as SIL 4.

Acceptance Test-Driven Development (ATDD) enhances both functional and non-functional aspects of the project, providing a collaborative approach to acceptance criteria that developers, testers, and stakeholders agree upon before development begins. Using ATDD alongside TDD (Test-Driven Development) ensures that both the internal system logic and the user-facing features adhere to the specified requirements, thereby increasing the likelihood of delivering a quality product that meets all stakeholders' expectations .

The primary consideration when selecting performance testing tools, especially for evaluating the capability to handle 10,000 concurrent users, is the ability of the tool to generate load at the communications protocol level. This feature allows the tool to simulate multiple users interacting with the server/backend without the overhead of running full client-side interactions, focusing on server capacity and response times​​.

A common technical issue causing automation projects to fail in delivering the planned return on investment is the lack of maintainability in their design. Automation frameworks and scripts that are not designed with maintainability in mind can become cumbersome to update and scale as the software evolves. This results in increased costs and effort over time to keep the automation relevant and effective, which can erode the expected returns on investment from the automation initiative .

In this scenario, the key stakeholders have expressed concerns related to performance, specifically in terms of the batch jobs and the ease of parameter entry for forecasting reports. Given these requirements, performance testing is essential to meet their objectives.

Objectives of the Stakeholders:

Merchandising Manager: Wants parameter entry to be quick and easy.

Data Centre Manager: Requires the new batch jobs to take less time than the old ones.

Best Testing Approaches:

Performance Testing on Forecasting Report Parameter Data Entry Features (Option A):

Conducting performance testing on the parameter data entry features ensures that the process is quick and efficient, meeting the Merchandising Manager’s requirement for ease of use.

Performance Testing on Data Load and Report Creation (Option B):

Conducting performance testing on data load and report creation will address the Data Centre Manager’s concern by ensuring that the batch jobs complete in less time compared to the old system.

Explanation of Incorrect Options:

C. Agreeing acceptance criteria for modifiability, modularity, and reusability: These criteria are more related to code quality and maintainability rather than performance, which is not the primary concern of the stakeholders.

D. Agreeing acceptance criteria for performance based on quantified improvement: While this is important, it’s not a testing activity itself but rather a prerequisite to performance testing.

E. Agreeing acceptance criteria based on operational profile models: This is also more related to planning and less about direct testing activities.

References:

The ISTQB CTAL-TTA syllabus outlines the importance of performance testing and stakeholder requirements in test planning and execution. Ensuring that performance tests are aligned with the key stakeholder objectives is crucial for successful project outcomes.

Sources:

ISTQB-CTAL-TTA Syllabus

General knowledge on performance testing and stakeholder requirement analysis.

The true statement about test automation is that test automation levels can be influenced by and can constrain the frequency of code deployments. This reflects the understanding that while test automation can speed up the validation of code changes, enabling more frequent deployments, it also requires that the automation is sufficiently robust to handle the pace and scope of these deployments without becoming a bottleneck​​.

Keyword-driven test automation is a framework where test cases are written using keywords that represent the actions or tests to be performed on the system. This is an extension of data-driven test automation, which focuses on separating test scripts from the test data, allowing the same test script to be run with various sets of data. Keyword-driven test automation further abstracts the process by allowing tests to be written in a more human-readable form that corresponds to business processes. This approach can improve maintainability and readability of test cases, making them easier to understand and modify. It’s not necessarily the case that one is more maintainable or easier to develop than the other (Options C and D); rather, they serve different purposes in test automation strategy.

API testing tends to focus on individual inputs more than combinations of inputs. This is because APIs, as the intermediary layers of software, often handle specific types of data input and output rather than user interaction sequences. GUI testing, on the other hand, involves testing the interface with which the user interacts, which frequently includes testing various combinations of user inputs and sequences to simulate actual user scenarios. Thus, GUI testing typically requires checking the integration and behavior of elements in combination to ensure they work together as expected in a user environment .