iSQI CTFL-AcT ISTQB Certified Tester - Acceptance Testing (CT-AcT) Exam Practice Test

Beta testing is a type of external user acceptance testing performed by potential or existing customers in a real-world environment. It typically occurs after internal validation and acceptance tests have been passed. The purpose is to validate the product in realistic contexts, identify usability issues, uncover defects that may have been missed in lab settings, and gather feedback for improvements.

Option C is correct because it best describes the intent and value of beta testing — to observe how the product performs in real-life configurations, which may include varying hardware, usage patterns, or business workflows.

Option A is incorrect — while some people use the terms loosely, beta testing is not a strict synonym for acceptance testing. Acceptance testing usually refers to more formal, criteria-driven testing (e.g., alpha or internal acceptance testing), while beta testing emphasizes broad, usage-based validation.

Option B is misleading — beta testers may follow scenarios, but beta testing is not typically based on predefined acceptance criteria alone. It emphasizes exploration in realistic use cases.

Option D is false — beta testing is not primarily about measuring test coverage. It is qualitative and feedback-driven rather than systematically structured.

Exact Reference – ISTQB CTFL Acceptance Testing Syllabus (Section 3.2):

“Beta testing is performed by users in their own environment and supports validation of the system in realistic operational conditions.”

Acceptance criteria describe the conditions under which a requirement or user story is considered fulfilled. These criteria serve as the basis for deriving acceptance test cases. To transform them into concrete tests, testers apply test design techniques such as:

Business process-based testing (deriving tests from modeled workflows)

Use case testing (based on user interactions with the system)

Option B is correct because it clearly describes how structured techniques are applied to translate acceptance criteria into actionable test cases, ensuring traceability and relevance.

Other options:

A is incorrect — experience-based techniques may supplement, but structured methods are foundational in deriving test cases from defined criteria.

C is misleading — risk-based testing is a well-established and effective practice for prioritizing test efforts, including acceptance testing.

D is incorrect — both functional and non-functional criteria are important; there’s no fixed rule to prioritize one over the other.

Answer: B. Test techniques such as business process-based testing or use case testing can be used to create acceptance tests from the acceptance criteria

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

Acceptance criteria must be concrete, testable, and focused on observable system behavior. They define what the system must do to satisfy a requirement and help determine whether the requirement has been successfully implemented.

REQ 3.28 states: “The automated system records critical credit application data (CCAD) needed to support application screening.” From this, we infer that the system must persistently store this data after data entry.

Option A is the best match because it provides a specific, observable behavior (CCAD being stored in a MySQL database after a successful entry) that can be verified through acceptance testing. It’s a measurable outcome, aligned with the requirement's objective.

Other options are less suitable:

Option B introduces new behavior (displaying a message) not directly tied to the original requirement.

Option C is vague ("quick and reversible") and lacks measurable criteria.

Option D refers to usability guidelines, which is not directly relevant to the storage functionality stated in the requirement.

Exact Reference – ISTQB CTFL Acceptance Testing Syllabus (Section 1.3.2):

“Well-written acceptance criteria are unambiguous, testable, and focused on observable results.”

Exploratory testing in Agile projects is a structured but unscripted testing approach where learning, test design, and execution occur simultaneously. Timeboxing is a key practice in managing exploratory testing sessions effectively.

A timebox is a fixed duration (e.g., 60–90 minutes) within which testers explore specific functionalities or risks. It encourages focus, documentation of findings, and prevents overrun or testing fatigue. After the session, testers often hold debriefs to review findings and determine next steps.

Option D is correct because timeboxing is essential for exploratory testing management.

Incorrect options:

A. Pair programming relates to development, not testing.

B. Refactoring is a development technique focused on improving code without changing behavior.

C. Planning poker is used in Agile for effort estimation, not directly related to exploratory testing.

Exact Reference – ISTQB CTFL Acceptance Testing Syllabus (Section 3.1):

“Exploratory testing is often conducted in time-boxed sessions, with a charter guiding the scope of the session.”

In BPMN models, additional annotations such as links to requirements, test data, or risks improve the value of the diagram for downstream stakeholders like testers. When BPMN tasks or flows are linked to known risks, testers can prioritize regression test cases accordingly — a key principle in risk-based testing.

Option D is correct because linking risks to business processes gives testers meaningful input for deciding which parts of the system require deeper or repeated testing.

Other options:

A: Priority links are useful, but less impactful than risk-based test selection.

B: Links to test equipment are not commonly embedded in process diagrams and are more relevant to hardware or system integration testing.

C: Linking to requirements helps traceability, but execution readiness is more closely tied to test cases and data than to BPMN.

Answer: D. Link to risks provide input to testers for selecting regression tests

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.)

Acceptance Test-Driven Development (ATDD) involves early collaboration between stakeholders to define acceptance criteria and tests before development begins. Using business process models in ATDD helps visualize user behavior, align test cases with real workflows, and serve as living documentation.

Option C is the least meaningful argument because:

Business process models abstractly describe workflows and decisions at a business level. While they help clarify requirements and detect requirement-related defects, they do not directly support detecting defects in the application code, which is typically the focus of unit and integration testing, not acceptance testing.

Let’s validate the other options:

A is a strong argument — process models clarify use cases for testers.

B is valid — graphical models help visualize test coverage directly.

D is true — as business process models evolve, they remain valuable artifacts aligned with current system behavior and requirements.

Answer: C. Business process models will make it easier to detect defects in the application code.

Let’s analyze the DMN table shown in the image:

Rule 1: If weight ≤15, size ≤50, and distance ≤10 → use Normal bicycle

Rule 2: If weight is between 15 and 60 kg, size ≤150, and distance ≤25 → use Electric cargo bike

Rule 3: Otherwise → use Electric van

Now consider the options:

A: Incorrect — parcel size is not the only determining factor for using electric vans; it's about weight, size, and distance combined.

B: Incorrect — normal bicycles are used only when weight ≤15 kg, size ≤50 cm, and distance ≤10 km — so not just “short trips.”

C: Incorrect — electric cargo bikes are explicitly used for short trips (≤25 km), per Rule 2.

D: Correct — based on the rules, any weight above 15 kg (and up to 60 kg) results in the use of electric cargo bikes. So if weight >50 kg (but ≤60), cargo bike is still used under the conditions of Rule 2.

Therefore, the most consistent interpretation of the decision model is:

Answer: D. When the weight of the parcel exceeds 50kg then the electric cargo bike is necessarily used

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

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

In usability and user experience, system feedback is critical. Users expect clear, timely responses from the system to confirm their actions are received and processed. Lack of feedback (e.g., when clicking a button yields no visual response) leads to confusion, frustration, or repeated actions.

Option B is correct because it highlights a genuine issue from a user’s perspective — inadequate feedback, which affects usability and satisfaction.

Other options:

A focuses on technical infrastructure (architecture, computing power) — a technical or business concern, but less so from a user’s lens.

C is mostly correct but fits the technical or test engineer’s perspective rather than the user’s.

D is inaccurate — selection of performance tools is primarily a technical/test management decision, not business-driven.

Answer: B. From a user perspective, missing feedback from the system when processing a request is a problem.

To determine the minimum number of test cases needed to cover:

All unique paths (without repeating loops) in the BPMN process model.

All decision rules (combinations) in the DMN decision table.

Let’s break it down:

BPMN Paths:

If the purchase order is not approved → process ends → 1 path

If approved:

Goods received → “Check of delivery” → Acceptance YES → Payment → 1 path

Goods received → “Check of delivery” → Acceptance NO → Discussion → End → 1 path

= Total distinct BPMN paths: 3

DMN Table:

There are 4 rules based on two inputs (Quality check and Quantity check):

Acceptable + Amount ok → Passed

Substandard + Amount ok → Failed

Acceptable + Amount incorrect → Failed

Substandard + Amount incorrect → Failed

You must execute 4 combinations to cover all decision rules.

To cover both all BPMN flows and all DMN rules, you need a minimum of 4 test cases (each using a different rule from the DMN table and associated BPMN path). Paths may overlap, but all rules must be exercised.

Comprehensive Detailed Explanation (Approx. 200 words):

Acceptance criteria should focus on business-relevant outcomes that are specific, testable, and observable. In this user story, the goal is to validate that the registration functionality is available and behaves as expected.

Let's analyze each proposition:

i) “A registration form is displayed on the screen.”

→ Valid. It is observable, specific, and directly aligned with the user story.

ii) “The form is written in the Groovy language; the cursor is initially set on the ‘login’ field...”

→ Invalid as acceptance criteria. It contains implementation details (e.g., “Groovy language”) irrelevant to business stakeholders. Also, low-level UI behavior like cursor position is overly technical and not a business-driven criterion.

iii) “I cannot register myself if the login I choose is used by another player.”

→ Valid. It defines system behavior based on a business rule (unique login) and is testable.

iv) “After successful registration process I am informed about it by an e-mail.”

→ Valid. It describes a user-visible outcome after registration, which is observable and testable.

Correct answer: D. only i), iii), and iv) are well-written acceptance criteria.

Exact Reference – ISTQB CTFL Acceptance Testing Syllabus (Section 1.3.2):

“Acceptance criteria must describe the externally visible and verifiable system behavior, excluding implementation details.”

Non-functional quality attributes (also called quality characteristics) such as usability, reliability, operability, performance, and maintainability are often validated during acceptance testing to ensure the system behaves as expected under real-world conditions.

Option C is correct because operability — a subcharacteristic of usability per ISO 25010 — refers to the degree to which users can operate and control the system effectively. Acceptance testing often involves running the system in realistic settings to validate these aspects.

Other options:

A (Modularity and reusability) are more relevant to system architecture and design, not acceptance testing.

B is incorrect — time behavior (performance) can and should be tested at multiple levels, including system and integration testing before acceptance.

D is misleading — testing basic functionality is necessary, but it does not address non-functional quality attributes.

Answer: C. During acceptance testing, the operability of the product is checked in a realistic environment

Traceability is a key principle in requirements and test management. It ensures that all features, requirements, and tests are linked and accounted for. Including traceability to user stories in BPMN diagrams or DMN tables supports transparency, auditability, and maintenance.

Option B is correct because embedding or referencing traceability information within business models improves communication across stakeholders, ensures proper test coverage, and helps during change impact analysis.

Let’s evaluate other options:

Option A is incorrect. Trying to place all model elements in one diagram can lead to cluttered and unreadable models.

Option C is misleading. While separation of concerns is useful, traceability (links to requirements, risks) should be integrated or closely accessible from the models.

Option D is incorrect. Acceptance testers should be involved early to collaborate and review models. Waiting until models are finalized contradicts agile and ATDD principles.

Answer: B. BPMN diagrams and DMN tables should include information such as traceability to user stories.

Performance testing assesses how a system behaves under specific conditions, typically focusing on responsiveness, stability, and resource usage. The type of performance test depends on the workload model:

Load testing evaluates performance under expected peak usage.

Stress testing pushes the system beyond its capacity to assess limits.

Endurance/stability testing checks for performance degradation over extended periods.

Option A correctly describes that performance test types are determined by the workload simulation strategy.

Other options:

B confuses performance with security testing — malicious attack robustness is a security focus, not performance.

C is partly correct but less comprehensive than A. While testing should simulate realistic conditions, categorization into stress/load/endurance is better aligned with workload modeling.

D is misleading — performance tests validate systems against performance requirements; they are not primarily used to define them.

Answer: A. Depending on the model used to simulate the workload, performance tests are called load, stress or endurance / stability tests.

Model-Based Testing (MBT) is a test design technique in which test cases are derived from a model that describes some aspects of the system’s behavior. In the context of acceptance testing, MBT can be used to generate high-level acceptance test cases automatically from business process models, use case diagrams, state models, or decision tables.

Option A is correct because MBT supports the systematic generation of acceptance test cases from these models, enabling better coverage of business rules and workflows while maintaining traceability to the requirements.

Other options:

B is close but slightly off: prioritization of acceptance tests in a priority-based approach depends on business value or stakeholder-defined priorities, not strictly on product risks.

C is incorrect. Risk-based testing relies on structured risk assessment, not just intuition or experience.

D is false. Black-box testing focuses on inputs and outputs without referencing the internal structure (such as function calls), which is characteristic of white-box testing.

Exact Reference – ISTQB CTFL Acceptance Testing Syllabus (Section 2.3):

“Model-based testing can be used to generate acceptance test cases systematically based on models representing business processes or system behavior.”

“Early Testing” is a well-known best practice in software testing, promoting the involvement of testers early in the project — ideally during requirements definition — to identify ambiguities, risks, and inconsistencies.

Option B is correct because involving both testers and business analysts in defining acceptance criteria helps ensure those criteria are clear, testable, and aligned with business needs from the outset. This leads to fewer misunderstandings and defects later in the lifecycle.

Other options:

A is incorrect — Agile does not eliminate requirements engineering; it adapts it with user stories, refinement, and just-in-time elaboration.

C is incorrect — test analysis interprets existing requirements; it doesn’t produce them.

D is false — while some level of test independence is valuable, Agile promotes collaboration between roles to achieve shared understanding.

Answer: B. The joint work of business analyst and testers on acceptance criteria and acceptance test cases contributes to the "Early Testing" best practice

The ISTQB CTFL Acceptance Testing Syllabus emphasizes the importance of collaboration between business analysts and testers throughout the testing lifecycle, especially during test planning and risk identification. Business analysts contribute domain knowledge and business context, which is crucial in identifying business-critical areas, defining priorities, and ensuring that acceptance tests align with business goals.

Option A correctly identifies this collaboration. During test planning, business analysts help define acceptance criteria, identify risks from a business perspective, and support test prioritization to focus on high-value features. Their early involvement ensures that acceptance tests are meaningful and support stakeholder expectations.

Option B is incorrect as business analysts actively review acceptance tests to confirm alignment with business rules, regardless of technical complexity.

Option C is inaccurate because although testers seek to understand business needs, the responsibility for identifying those needs lies with business analysts.

Option D is incorrect; business analysts remain engaged throughout the project lifecycle, including test support and defect triage.

Exact Reference – ISTQB CTFL Acceptance Testing Syllabus (Section 1.4):

“Testers and business analysts collaborate during test planning and analysis activities to ensure the tests meet business needs and risk areas are adequately covered.”

Therefore, A provides the most accurate and comprehensive description.

Comprehensive Detailed Explanation:

According to the scenario described in the question, the business process for expense reimbursement includes two key timing constraints:

If the request is not processed within 7 days, an "ongoing" email is sent to the employee.

If the request is not completed within 30 days, the process is canceled and the employee is asked to resubmit the request.

However, in the BPMN model presented in the image, the second timing event (clock icon near "Approval in Progress") incorrectly shows 23 days instead of 30 days. This discrepancy misrepresents the actual business rule and violates the accuracy required in process modeling.

ISTQB Foundation Level Extension – Acceptance Testing syllabus and the Certified Tester Foundation Level Business Process Testing (CTFL-BAT) emphasize that a process model should correctly reflect the specified behavior, rules, and constraints of the business scenario. An incorrect timer can lead to miscommunication between stakeholders and incorrect automation or implementation logic.

Therefore, Option A is the most likely review comment since it directly points to this inconsistency in the model.

ATDD and BDD are agile development approaches that emphasize collaboration among stakeholders (such as business analysts, developers, testers, and customers) to define clear and testable acceptance criteria before or as requirements are being finalized. Both techniques promote using concrete examples to drive development and validate understanding.

In ATDD, acceptance test cases are derived directly from user stories or requirements and written before the actual implementation starts. In BDD, scenarios are expressed in natural language (often using Gherkin syntax) to describe behaviors the system should exhibit under specific conditions. In both cases, these tests serve not only as validation tools but also as executable specifications — i.e., shared understanding expressed through concrete examples.

Option B is correct because both methodologies use examples (scenarios/test cases) to describe how a system should behave — serving as acceptance criteria.

Incorrect options:

Option A wrongly suggests BDD defers testing until after requirements are finalized — it actually promotes early collaboration.

Option C is false — in ATDD, test cases are based on predefined acceptance criteria, not written beforehand.

Option D is inaccurate — acceptance tests in ATDD and BDD may be automated but are collaboratively written first, not by test automation engineers alone.

Exact Reference – ISTQB CTFL Acceptance Testing Syllabus (Section 2.2):

“Both ATDD and BDD involve the collaborative definition of test cases before implementation to clarify requirements and serve as product usage examples.”

In ATDD (Acceptance Test-Driven Development), business process modeling (e.g., using BPMN) is a powerful way to visualize workflows and system behavior from the user's perspective. Testers can use these models to derive acceptance test cases by covering different business paths, including normal flows, alternate flows, and exception conditions.

Option A is correct because it reflects this practical usage: testers analyze the business process model and create test cases to ensure coverage of the different paths the system might take. This aligns acceptance testing directly with business logic and enhances traceability.

Other options:

B is partially valid but less direct; business analysts help define rules, but test case creation is a tester's role.

C reverses the correct flow; BPMN models are often created first and used to define or validate acceptance criteria, not the other way around.

D is incorrect — requirements/user stories are usually defined through stakeholder collaboration, not auto-generated from BPMN diagrams.

Answer: A. Testers use business process models to write test cases that cover the different paths.

Defect reporting is a core responsibility of testers. When a test fails, the tester must document the observed behavior and how it differs from the expected behavior. This allows developers, analysts, and stakeholders to assess whether the issue is a defect, and if so, prioritize and fix it.

Option B is correct because it accurately describes the core responsibility of a tester when logging a defect: report the mismatch between actual and expected outcomes clearly and objectively.

Other options:

A refers to meetings, which are useful but not a replacement for clear defect reports.

C incorrectly assigns the role of defect routing to business analysts — this is typically handled by test or defect management tools.

D suggests the tester analyzes impact before reporting — which could delay the defect being logged and is not always the tester's role (impact analysis is often done collaboratively later).

Answer: B. Testers should provide accurate information regarding the difference between the expected test result and the actual result.