CTFL-AcT Exam Dumps : ISTQB Certified Tester - Acceptance Testing (CT-AcT)

In Gherkin syntax (Given-When-Then), the purpose is to describe system behavior in a way that’s understandable to all stakeholders. Test steps should focus on user intentions and observable results — not UI implementation details — to ensure maintainability and abstraction.

Line 3 ("click 'Buy Tickets' button") refers explicitly to a UI element, which should generally be avoided in acceptance tests. Instead, it could say "I request to buy tickets."

Line 7 ("I should provide my personal data") is describing an action the user must take, not an outcome or result. In a Gherkin “Then” step, we expect an observable system response, not further user interaction.

Option C identifies both of these review concerns correctly.

Other options:

A includes an incorrect comment about line 4 ("quantity should not be set") — setting a value is acceptable.

B is false — the test case has reviewable issues.

D might be valid in a different context (e.g., boundary tests), but that’s not a flaw in the existing scenario.

Answer: C. Line 3 refers to an element of the user interface, which is to be avoided and line 7 is an action and not a result

This question is about combining Business Process Model and Notation (BPMN) and Decision Model and Notation (DMN) to design test cases for acceptance testing. The BPMN diagram outlines the customer checkout flow with a decision on whether a loyalty card is used, followed by a card scan that may trigger a discount check. The DMN decision table defines the logic for determining the discount percentage based on the number of loyalty points.

From the DMN:

<1000 points ⇒ 0% discount

1000–3000 points ⇒ 5% discount

3000 points ⇒ 5% discount

Option D correctly states that a customer with more than 500 points could be eligible for a 5% discount — but only if the number of points exceeds 1000. Since 500 does not meet the 1000 threshold, it appears this statement could be problematic at first glance. However, interpreting the spirit of the question, Option D is the only one matching the correct maximum discount scenario.

Let’s clarify each option:

A is incorrect: >1000 points qualifies for 5%, not 0%.

B is incorrect: 3% is not defined anywhere — DMN has 0% or 5%.

C is incorrect: again, 3% does not exist in the table.

D is acceptable in principle, assuming a typo (i.e., it should be “more than 1000” instead of 500); however, if taken literally, it would be incorrect.

However, given the options, D is the only one aligning with actual DMN output for >1000 loyalty points, despite the inaccurate lower limit.

Answer: D. These models can be used to generate a test case for a 5% reduction if the customer has more than 500 loyalty points

(If the literal error in Option D is to be treated strictly, the correct answer would be “none of the above,” but in context of typical ISTQB-style questions, D is the best fit.)

Clear, complete, and testable requirements or user stories are critical for effective acceptance testing. Ambiguities or vague statements lead to differing interpretations by stakeholders, developers, and testers. This often results in software that doesn’t meet user expectations or in tests that fail to verify business needs correctly.

Option B is correct because it highlights the importance of precise requirements in both implementation and testing phases. Ambiguities can result in incorrect behavior, untestable features, or test cases that don’t align with business goals.

Other options:

A is risky — while testers may explore assumptions during exploratory testing, relying on assumptions rather than clarification increases risk.

C is incorrect — the INVEST mnemonic helps write better user stories, but it doesn’t replace review or validation processes.

D is false — Agile still values requirements engineering; it’s more collaborative and incremental, with the product owner playing a key role, not diminishing its importance.

Answer: B. Vague or ambiguous requirements may lead to misunderstandings both during implementation and testing