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

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.)

The goal here is to achieve full decision coverage (also known as branch coverage), which means each decision point in the process must evaluate to both TRUE and FALSE at least once during testing.

From the BPMN ATM withdrawal model, we identify two key decisions:

Is the balance ≥ $100?

If yes, is receipt = YES?

To achieve full decision coverage:

One test must evaluate decision 1 as TRUE and another as FALSE.

If decision 1 is TRUE, then decision 2 must be exercised both ways (receipt = YES and NO), but for minimal decision coverage, one path through decision 2 is enough.

Analyzing test cases:

Test 1 (balance = $100, receipt = YES): decision 1 = TRUE, decision 2 = TRUE

Test 2 (balance = $99): decision 1 = FALSE

These two tests ensure:

Decision 1 evaluated TRUE (Test 1) and FALSE (Test 2)

Decision 2 evaluated at least once (receipt = YES in Test 1)

Thus, Test 1 and Test 2 form the minimal set for full decision coverage.

Other options:

C and D are redundant for the minimal set.

A includes an extra test not needed for minimal decision coverage.

Answer: B. Test 1, Test 2

User Experience (UX) requirement analysis is a critical component of acceptance testing and product development. According to ISTQB Acceptance Testing syllabus and industry-aligned UX design methodologies (e.g., ISO 9241-210 and BABOK guidelines), UX requirement analysis is typically structured around the following pillars:

User Analysis – Understanding who the users are (roles, goals, experience levels)

Task Analysis – Understanding what users do (tasks, workflows, pain points)

Context Analysis – Understanding where and how users interact with the product (environmental and contextual factors)

Competitor Analysis – Understanding how similar problems are solved in the market

Option B best describes Task Analysis, one of the most practical and impactful pillars. In task analysis, business analysts and UX researchers observe how users interact with current or comparable systems to understand workflow patterns, user frustrations, needs, and required system functionality. This method helps uncover implicit needs that users may not articulate in interviews.

This approach is aligned with ISTQB’s emphasis on understanding real-world usage and business processes as a foundation for deriving acceptance criteria and tests. It supports the creation of realistic scenarios that reflect actual user behavior, which is essential for verifying system fitness for use.

The other options are inaccurate:

A refers to psychological disposition, which is more aligned with user profiling or persona development, not a core focus of user analysis in requirement engineering.

C incorrectly ties context analysis with deriving security requirements, which is not its purpose.

D describes an unrealistic or incorrect method for competitor analysis.

Therefore, Option B is the best description of a key pillar of UX requirement analysis per industry and ISTQB standards.