ISTQB-CTFL Practice Exam Questions with Answers ISTQB Certified Tester Foundation Level (CTFL) v4.0 Certification

A software bug can cause harm to a company by directly affecting its operations, reputation, user satisfaction, and financials. Option D, "When calculating the final price in a shopping list, the price of the last item is not added," describes a defect that directly impacts the core functionality of a financial transaction, potentially leading to financial loss and customer dissatisfaction. This can have severe implications for the company's credibility and revenue. Options A, B, and C describe bugs that, while potentially annoying, do not have the same direct impact on the company's core operations and financial integrity as option D.

An incident is any event that occurs during testing that requires investigation. An incident report is a document that records the details of an incident. The next step the tester should take prior to recording the deviation is to try to recreate the incident before reporting. This can help confirm that the incident is reproducible and not caused by a random or external factor. This can also help gather more information about the incident, such as the steps to reproduce it, the expected and actual results, the severity and priority of the incident, or any screenshots or logs that can illustrate the incident. Trying to identify the code fragment causing the problem is not the next step the tester should take prior to recording the deviation, as this is a debugging activity that is usually performed by developers after receiving the incident report. Sending an email to the developer and not reporting the bug is not the next step the tester should take prior to recording the deviation, as this is an informal and unstructured way of communicating incidents that can lead to confusion, inconsistency or loss of information. Reporting the incident as is without any further action is not the next step the tester should take prior to recording the deviation, as this can result in incomplete or inaccurate incident reports that can hamper the investigation and resolution of incidents. Verified References: A Study Guide to the ISTQB® Foundation Level 2018 Syllabus - Springer, Chapter 3, page 32-33.

In the context of agile (iterative-incremental) development models, testing is integrated into the development process and occurs continuously throughout the lifecycle of the project. Agile testing emphasizes adaptability and the need for feedback at various stages of development.

Option C is correct because regression testing is indeed necessary whenever a new increment is added to the existing system. Agile development often involves frequent changes and additions to the codebase, which can potentially introduce new defects into previously tested code. Regression testing ensures that new changes have not adversely affected existing functionality.

Options A, B, and D present misconceptions about agile testing:

• A is incorrect because, in agile, all types of testing (unit, integration, system, acceptance) are important and occur throughout the iteration, not just unit and acceptance tests.
• B is incorrect because agile methodologies advocate for continuous integration and testing, where development and testing activities overlap and support each other throughout an iteration.
• D is incorrect because agile methodologies encourage a wide range of testing types, including both functional and non-functional, as well as exploratory testing, to ensure a comprehensive quality assessment.

 Functional testing is an example of black-box dynamic testing. Black-box testing (also known as specification-based testing) is a type of testing that does not consider the internal structure or implementation of the system under test, but rather its external behavior or functionality. Dynamic testing is a type of testing that involves executing the system under test with various inputs and observing its outputs. Functional testing is a type of black-box dynamic testing that verifies that the system under test performs its intended functions according to its requirements or specifications. Functional testing can be performed at various levels and scopes depending on the objectives and criteria of testing. The other options are not examples of black-box dynamic testing. Code inspection is an example of white-box static testing. White-box testing (also known as structure-based testing) is a type of testing that considers the internal structure or implementation of the system under test. Static testing is a type of testing that does not involve executing the system under test, but rather analyzing it for defects, errors, or violations of standards. Code inspection is a type of white-box static testing that involves examining the source code of the system under test for quality, readability, maintainability, etc. Checking memory leaks for a program by executing it is an example of white-box dynamic testing. Memory leaks are defects that occur when a program fails to release memory that it has allocated but no longer needs. Checking memory leaks for a program by executing it requires knowledge and access to the internal structure or implementation of the program, such as memory allocation and deallocation mechanisms, pointers, references, etc. Coverage analysis is an example of white-box static testing. Coverage analysis is a technique that measures how much of the code or structure of the system under test has been exercised by a test suite. Coverage analysis requires knowledge and access to the internal structure or implementation of the system under test, such as statements, branches, paths, conditions, etc. Verified References: A Study Guide to the ISTQB® Foundation Level 2018 Syllabus - Springer, page 7.

The correct set of data for valid equivalence class partitions should include one value from each equivalence class, and no value from outside the range. Option C satisfies this condition, as it has one value from each of the four equivalence classes (50, 100, 250, 500). Option A has two values from the same equivalence class (100 and 200), option B has values outside the range (0 and 0.99), and option D has two values from the same equivalence class (1000 and 500). Verified References: A Study Guide to the ISTQB® Foundation Level 2018 Syllabus - Springer, page 35.

Covering all transitions at least once is the highest coverage criterion for state transition based test cases, because it ensures that every possible change of state is tested at least once. This means that all the events that trigger the transitions, as well as the actions and outputs that result from the transitions, are verified. Covering all transitions at least once also implies covering all states at least once, but not vice versa. Therefore, option D is not the highest coverage criterion. Option C is the lowest coverage criterion, because it only tests the initial and final states of the system or component, without checking the intermediate states or transitions. Option A is incorrect, because the coverage criteria for state transition based test cases can be determined and compared based on the number of transitions and states covered. References = CTFL 4.0 Syllabus, Section 4.2.3, page 49-50.

 The thought process of the software company is incorrect, because it assumes that each artifact can be reviewed using only one review method, and that the review method depends solely on the criticality of the artifact. This is a simplistic and rigid approach that does not consider the benefits and limitations of different review methods, the context and purpose of the review, and the feedback and improvement opportunities that can be gained from multiple reviews. According to the CTFL 4.0 Syllabus, the selection of review methods should be based on several factors, such as the type and level of detail of the artifact, the availability and competence of the reviewers, the time and budget constraints, the expected defects and risks, and the desired outcomes and quality criteria. Moreover, the same artifact can be reviewed using different review methods at different stages of the development lifecycle, to ensure that the artifact meets the changing requirements, standards, and expectations of the stakeholders. For example, a requirement specification can be reviewed using an informal review method, such as a walkthrough, to get an initial feedback from the users and developers, and then using a formal review method, such as an inspection, to verify the completeness, correctness, and consistency of the specification. Therefore, the software company should adopt a more flexible and context-sensitive approach to selecting and applying review methods for different artifacts, rather than following a fixed and arbitrary rule. References = CTFL 4.0 Syllabus, Section 3.2.1, page 31-32; Section 3.2.2, page 33-34; Section 3.2.3, page 35-36.

Statement coverage is a structural coverage metric that measures the percentage of executable statements in the source code that are executed by a test suite1. Decision coverage is another structural coverage metric that measures the percentage of decision outcomes (such as branches or conditions) in the source code that are executed by a test suite1. Decision coverage is a stronger metric than statement coverage, because it requires that every possible outcome of each decision is tested, while statement coverage only requires that every statement is executed at least once2. Therefore, if a test suite achieves 100% decision coverage, it also implies that it achieves 100% statement coverage, because every statement in every branch or condition must have been executed. However, the converse is not true: 100% statement coverage does not guarantee 100% decision coverage, because some branches or conditions may have multiple outcomes that are not tested by the test suite2. For example, consider the following pseudocode:

if (x > 0) then print(“Positive”) else print(“Non-positive”) end if

A test suite that executes this code with x = 1 and x = -1 will achieve 100% statement coverage, because both print statements are executed. However, it will not achieve 100% decision coverage, because the condition x > 0 has only been tested with two outcomes: true and false. The third possible outcome, x = 0, has not been tested by the test suite. Therefore, the test suite may miss a potential bug or error in the condition or the branch.

The other options, such as stale transition coverage, equivalence class coverage, and boundary value coverage, are not guaranteed to be 100% by achieving 100% decision coverage. Stale transition coverage is a structural coverage metric that measures the percentage of transitions between states in a state machine that are executed by a test suite3. Equivalence class coverage is a functional coverage metric that measures the percentage of equivalence classes (or partitions) of input or output values that are tested by a test suite4. Boundary value coverage is another functional coverage metric that measures the percentage of boundary values (or extreme values) of input or output ranges that are tested by a test suite4. These metrics are independent of decision coverage, because they are based on different aspects of the system under test, such as its behavior, functionality, or specification. Therefore, achieving 100% decision coverage does not imply achieving 100% of any of these metrics, and vice versa. References = ISTQB® Certified Tester Foundation Level Syllabus v4.0, Test Coverage in Software Testing - Guru99, Structural Coverage Metrics - MATLAB & Simulink - MathWorks India, Test Design Coverage in Software Testing - GeeksforGeeks.

A decision table is a technique that should be used to cover all possible combinations of input conditions for withdrawing money from an Automated Teller Machine (ATM). A decision table shows combinations of inputs and/or stimuli (causes) with their associated outputs and/or actions (effects). A decision table consists of four quadrants: conditions (inputs), actions (outputs), condition entries (values) and action entries (results). A decision table can be used to test components that have multiple inputs and outputs that depend on logical combinations of conditions. For example, for testing the ATM, we can identify three input conditions: the bank card is valid, the PIN code is correct, and money is available in the user’s account. We can also identify four output actions: the card is rejected, the ATM asks for another PIN code, the ATM asks for another amount, and the ATM dispenses the money. A decision table can show all possible combinations of these conditions and actions in a systematic way.

Use case based testing is not a technique that can cover all possible combinations of input conditions for withdrawing money from an ATM. Use case based testing is a technique that verifies that a software product or system meets its specified requirements or user stories by executing realistic scenarios or workflows. Use case based testing can be used to test components that have complex or dynamic interactions with users or other systems. For example, for testing the ATM, we can identify several use cases, such as withdraw money, check balance, transfer money, etc. Each use case can have one or more scenarios that describe the steps and outcomes of the interaction. However, use case based testing may not cover all possible combinations of input conditions, as some scenarios may be omitted or overlooked.

Boundary value analysis is not a technique that can cover all possible combinations of input conditions for withdrawing money from an ATM. Boundary value analysis is a technique that tests boundary values between partitions of equivalent data. Boundary values are values at the edge of an equivalence partition or at the smallest incremental distance on either side of an edge. Boundary value analysis can be used to test components that have input values that can be divided into partitions of equivalent data. For example, for testing the ATM, we can identify boundary values for the input amount, such as the minimum and maximum amount allowed by the system or the user’s account. However, boundary value analysis may not cover all possible combinations of input conditions, as some conditions may not have boundary values or may not be related to input values.

Equivalence class partitioning is not a technique that can cover all possible combinations of input conditions for withdrawing money from an ATM. Equivalence class partitioning is a technique that divides the input data and output results of a software component into partitions of equivalent data. Each partition should contain data that is treated in the same way by the component. Equivalence class partitioning can be used to test components that have input values that can be divided into partitions of equivalent data. For example, for testing the ATM, we can identify equivalence partitions for the input amount, such as valid amount (within the range allowed by the system and the user’s account) and invalid amount (outside the range allowed by the system or the user’s account). However, equivalence class partitioning may not cover all possible combinations of input conditions, as some conditions may not be related to input values or may have more than two partitions. Verified References: [A Study Guide to the ISTQB® Foundation Level 2018 Syllabus - Springer], Chapter 4, page 34-46.

A typical product risk involves issues directly related to the software product's functionality, performance, usability, reliability, etc. Option A, "Poor usability of the software," directly impacts the end-user's interaction with the software and is a quality attribute of the product itself, making it a product risk. Options B, "A problem in the code developed by a 3rd party," C, "Low quality of the configuration data, test data and tests," and D, "Problem in defining the right requirements," can be considered either product or project risks depending on the context, but option A is the most directly associated with a typical product risk concerning the quality and usability of the software.

This question relates to identifying product risks, which are potential problems associated with the product itself, such as software functionality, reliability, usability, and performance. Option A describes a scenario where the application might not meet performance requirements under specific conditions (up to 300 concurrent users), which directly impacts the product's ability to perform its intended function. This is a classic example of a product risk, as it concerns the product's quality and its ability to meet user needs. Options B, C, and D, on the other hand, relate to project risks, which are concerns related to the management and execution of the project, such as tool acquisition, environment configuration, and team expertise, rather than the quality of the product itself.

An exit criterion is a condition that defines when a test activity has been completed or when a test phase can be concluded. An exit criterion can be based on various factors, such as:

• I) Estimates of defect density or reliability measures. These are quantitative measures that indicate how many defects are present in the software product or how likely it is to fail under certain conditions. These can be used as exit criteria to ensure that the software product meets a certain level of quality or performance before moving to the next phase or releasing it to the customer.
• III) Accuracy measures, such as code coverage, functionality coverage or risk coverage. These are quantitative measures that indicate how much of the software product has been tested in terms of its code, functionality or risk. These can be used as exit criteria to ensure that the test suite is adequate or complete before moving to the next phase or releasing it to the customer.
• IV) Residual risks, such as lack of code coverage in certain areas, unresolved defects or unknown factors. These are qualitative measures that indicate the remaining risks or uncertainties associated with the software product after testing. These can be used as exit criteria to ensure that the residual risks are acceptable or manageable before moving to the next phase or releasing it to the customer. The following factor is not a valid exit criterion:
• II) The completion and publication of an exhaustive Test Report. This is not a valid exit criterion, as it does not reflect the quality or completeness of the testing process or product. A test report is a document that summarizes the results and outcomes of a test activity or phase. A test report can be used as an input for deciding whether to exit a test activity or phase, but it is not a condition that defines when to exit. Verified References: A Study Guide to the ISTQB® Foundation Level 2018 Syllabus - Springer, Chapter 2, page 13; Chapter 6, page 58-59.

Option D correctly explains what is represented by the lines A, B and the axes X, Y in a testing metrics chart. According to option D:

• X-axis represents Time
• Y-axis represents Count
• Line A represents Number of open bugs
• Line B represents Total number of executed tests

This information is essential in understanding and analyzing the testing metrics of a completed project.

References: ISTQB Certified Tester Foundation Level (CTFL) v4.0 Syllabus, Section 2.5.1, Page 35.

 A test oracle is a mechanism or principle that can be used to determine whether the observed behavior or output of a system under test is correct or not1. A test oracle can be based on various sources of expected results, such as specifications, user expectations, previous versions, comparable systems, etc2. References: ISTQB Certified Tester Foundation Level (CTFL) v4.0 Syllabus, Section 1.2.1, Page 91; ISTQB Glossary of Testing Terms, Version 4.0, Page 332.

The key difference between a peer review of code and static analysis of code using a tool lies in their approaches and scope. A peer review is a manual inspection of the code by peers or colleagues, focusing not only on the technical aspects of the code but also on other elements such as design, compliance with standards, and maintainability. Peer reviews can identify defects, suggest improvements, and ensure that the code adheres to best practices and team standards.

On the other hand, static analysis is an automated process performed by tools designed to analyze the code without executing it. These tools can detect potential issues such as syntax errors, vulnerabilities, and code smells based on predefined rules and patterns. While static analysis is technically focused, it lacks the broader perspective that human reviewers can provide, such as evaluating the code's maintainability or adherence to project-specific standards. Therefore, static analysis targets the code technically, whereas peer review encompasses a wider range of aspects, making option B the correct answer.

The figure depicts the life-cycle of a defect using state transition testing. State transition testing is a technique that models how a system transitions from one state to another depending on events or conditions. The figure shows six states (S0 to S5) and seven transitions (T0 to T6). The correct sequence of state transitions that follows the figure is S0->S1->S2->S3->S5->S1->S2->S3. This sequence represents the following scenario:

• S0: The defect is not yet detected (initial state).
• T0: The defect is detected by testing (event).
• S1: The defect is reported and registered (state).
• T1: The defect is assigned to a developer for fixing (event).
• S2: The defect is being fixed by the developer (state).
• T2: The developer fixes the defect and delivers a new version (event).
• S3: The defect is verified by testing (state).
• T5: The testing fails to confirm that the defect is fixed (event).
• S5: The defect is rejected by testing (state).
• T6: The defect is reassigned to a developer for fixing (event).
• S1: The defect is reported and registered (state).
• T1: The defect is assigned to a developer for fixing (event).
• S2: The defect is being fixed by the developer (state).
• T2: The developer fixes the defect and delivers a new version (event).
• S3: The defect is verified by testing (state). The other sequences are incorrect, as they do not follow the transitions shown in the figure. Verified References: [A Study Guide to the ISTQB® Foundation Level 2018 Syllabus - Springer], Chapter 4, page 40-41.

Static analysis is a technique that analyzes the source code or other software artifacts without executing them. Static analysis can detect defects such as syntax errors, coding standards violations, potential security vulnerabilities, or logical flaws. Static analysis can catch the bug in the first implementation, as it contains two syntax errors: the variable y is declared twice, and the assignment statement X = y=z is invalid. Static analysis cannot catch the bugs in the other three implementations, as they are logical errors that do not violate any syntax rules, but produce incorrect results. Verified References: [A Study Guide to the ISTQB® Foundation Level 2018 Syllabus - Springer], Chapter 3, page 25-26.

Branch coverage is a type of structural coverage metric that measures the percentage of branches or decision outcomes that are executed by the test cases. A branch is a point in the code where the control flow can take two or more alternative paths based on a condition. For example, an if-else statement is a branch that can execute either the if-block or the else-block depending on the evaluation of the condition. Branch coverage ensures that each branch is taken at least once by the test cases, and thus reveals the behavior of the software under different scenarios. Branch coverage is also known as decision coverage or all-edges coverage.

Branch coverage is suitable for testing the cases where a specific action is not allowed, because it can verify that the test cases cover all the possible outcomes of the conditions that determine the action. For example, if the program has a condition that checks if the manufacturing stage can be stopped, then branch coverage can ensure that the test cases cover both the cases where the stage can be stopped and where it cannot be stopped. This way, branch coverage can help identify any missing or incorrect branches that may lead to undesired or unsafe actions.

The other options are not correct because they are not suitable for testing the cases where a specific action is not allowed. Code coverage is a general term that encompasses various types of coverage metrics, such as statement coverage, branch coverage, data flow coverage, etc. Code coverage does not specify which type of coverage metric is used for the analysis. Data flow coverage is a type of structural coverage metric that measures the percentage of data flow paths that are executed by the test cases. A data flow path is a sequence of statements that define, use, or kill a variable. Data flow coverage is useful for testing the correctness and completeness of the data manipulation in the software, but not for testing the conditions that determine the actions. Statement coverage is a type of structural coverage metric that measures the percentage of statements or lines of code that are executed by the test cases. Statement coverage ensures that each statement is executed at least once by the test cases, but it does not reveal the behavior of the software under different scenarios. Statement coverage is a weaker criterion than branch coverage, because it does not account for the branches or decision outcomes in the code. References = ISTQB Certified Tester Foundation Level (CTFL) v4.0 syllabus, Chapter 4: Test Techniques, Section 4.3: Structural Testing Techniques, Pages 51-54.

Statement B contradicts the general principles of testing, because running the same test set more often will not increase the chances of finding new defects, unless there are some changes in the system or environment that affect the test results. Running different test sets with different inputs, outputs or conditions would be more effective in finding new defects. Statements A, C and D are consistent with the general principles of testing. Statement A states that most defects are found in a small subset of a system’s modules, which is true according to the defect clustering principle. Statement C states that testing is better if it starts at the beginning of a project, which is true according to the early testing principle. Statement D states that how testing is done, is based on the situation in a particular project, which is true according to the context-dependent testing principle. Verified References: A Study Guide to the ISTQB® Foundation Level 2018 Syllabus - Springer, pages 4-6.

Use case testing is a technique that helps identify test cases that exercise the whole system on a transaction by transaction basis from start to finish. Use cases are descriptions of how users interact with the system to achieve a specific goal. Use case testing is not focused on data flow, but rather on process flow. Use case testing can be performed by professional testers, customers or end users, depending on the context. Use case testing does not require the test cases to be designed by customers or end users, but rather by anyone who has access to the use case specifications. Verified References: A Study Guide to the ISTQB® Foundation Level 2018 Syllabus - Springer, Chapter 4, page 36.

According to the ISTQB Certified Tester Foundation Level (CTFL) v4.0, the life cycle of a defect typically follows a sequence from its discovery to its closure. In the provided figure, it starts with S0 (New), moves to S1 (Assigned), then to S2 (Resolved), followed by S3 (Verified). If the defect is not fixed, it can be Re-opened (S5) and goes back for verification (S3). Once verified, it is Closed (S4). References: ISTQB Certified Tester Foundation Level (CTFL) v4.0 Syllabus, Section 1.4.3, Page 17.

To achieve 100% branch coverage of the process flow, we need to test both the true and false outcomes of the condition (User presses Cancel). Branch coverage is a type of structural testing that measures how many decision outcomes in a program have been executed by a test suite. Branch coverage can be used to assess the adequacy or completeness of a test suite.

To test the true outcome of the condition, we need a test case that simulates the user pressing Cancel after booking a bill. This test case will exit the loop and end the process flow.

To test the false outcome of the condition, we need a test case that simulates the user not pressing Cancel after booking a bill. This test case will repeat the loop and book another bill.

Therefore, we need at least two test cases to achieve 100% branch coverage of the process flow. One test case for each possible outcome of the condition.

Verified References: [A Study Guide to the ISTQB® Foundation Level 2018 Syllabus - Springer], Chapter 4, page 40-41.

A dynamic analysis tool is a tool that performs analysis of a software product based on its behavior during execution. A dynamic analysis tool can monitor various aspects of a program’s run-time performance, such as memory usage, CPU load, response time, or resource leaks. A dynamic analysis tool can monitor the allocation, use and de-allocation of memory during run-time of a program, which can help detect defects such as memory leaks, buffer overflows, or memory corruption. A dynamic analysis tool cannot provide support for traceability of tests, test results and incidents to source documents, as this is a function of a test management tool. A dynamic analysis tool cannot execute programs step-by-step in order to reproduce failures and find corresponding defects, as this is a function of a debugging tool. A dynamic analysis tool cannot provide support for release of baselines consisting of configuration items, as this is a function of a configuration management tool. Verified References: [A Study Guide to the ISTQB® Foundation Level 2018 Syllabus - Springer], Chapter 6, page 56-57.

Cost can be regarded as an exit criterion for testing, because it is a factor that affects the profitability and feasibility of the software product. Testing is an investment that aims to improve the quality and reliability of the software product, but it also consumes resources, such as time, money, and human effort. Therefore, testing should be planned and executed in a way that balances the cost and benefit of testing activities. Having cost as an exit criterion helps to avoid spending too much money on testing, which may result in an unprofitable product or a loss of competitive advantage. Cost can also help to prioritize and focus the testing efforts on the most critical and valuable features and functions of the software product. However, cost should not be the only exit criterion for testing, as it may not reflect the true quality and risk level of the software product. Other exit criteria, such as defect rate, test coverage, user satisfaction, etc., should also be considered and defined in the test plan.

The other options are incorrect, because they either deny the importance of cost as an exit criterion, or they make false or unrealistic assumptions about the cost of testing. Option B is incorrect, because the financial value of product quality can be estimated, for example, by using cost-benefit analysis, return on investment, or cost of quality models. Option C is incorrect, because going by cost as an exit criterion does not necessarily constrain the testing project or help achieve the desired quality level. Cost is a relative and variable factor that depends on the scope, complexity, and context of the software product and the testing project. Option D is incorrect, because the cost of testing can be measured effectively, for example, by using metrics, such as test effort, test resources, test tools, test environment, etc.

Component testing (also known as unit testing or module testing) is a level of testing that focuses on verifying the functionality and quality of individual software components (such as modules, classes, functions, methods, etc.). Component testing mainly tests interfaces and interaction between components, as well as internal logic and data structures of the components. Component testing may be applied using a test-first approach (such as test-driven development or behavior-driven development), where tests are written before the code is implemented. Component testing does not identify defects in modules and classes, as this is a result of component testing, not an objective. Simulators and stubs may be required for component testing, as they can simulate or replace missing or incomplete components or external systems that are needed for testing. Verified References: A Study Guide to the ISTQB® Foundation Level 2018 Syllabus - Springer, page 19.

An incident is any event that occurs during testing that requires investigation. An incident management tool is a software tool that supports recording and tracking incidents throughout their life cycle. A QA manager of a start-up company needs to implement within a week a low cost incident management tool. The best option for this case is to manage the incidents in a spreadsheet posted on the intranet. This option has several advantages over other options:

• It is low cost, as it does not require purchasing any additional software or hardware.
• It is easy to implement within a week, as it does not require installing or configuring any complex software or hardware.
• It is accessible and transparent, as it can be viewed and updated by anyone who has access to the intranet.
• It is structured and organized, as it can store and display various information about incidents, such as identifier, summary, description, severity, priority, status, resolution, etc. The other options are not suitable for this case, as they have several disadvantages over the chosen option:
• Documenting incidents on a large board in the lab is not a good option, as it is not accessible or transparent to anyone who is not physically present in the lab. It is also not structured or organized, as it may not store or display all the necessary information about incidents.
• Purchasing and deploying an incident management tool is not a good option, as it is not low cost or easy to implement within a week. It may require spending a significant amount of money and time on acquiring, installing and configuring the software or hardware.
• Managing the incidents through emails and phone calls is not a good option, as it is not structured or organized. It may lead to confusion, inconsistency or loss of information about incidents. Verified References: A Study Guide to the ISTQB® Foundation Level 2018 Syllabus - Springer, Chapter 3, page 32-33.

Equivalence partitioning is a technique that divides the input data and output results of a software component into partitions of equivalent data. Each partition should contain data that is treated in the same way by the component. Equivalence partitioning can be used to reduce the number of test cases by selecting one representative value from each partition. Equivalence partitioning is suitable for testing the price computation, as it can identify different partitions based on the passenger type, the travelling type, the distance and the kind of transport. Equivalence partitioning is not statement coverage, which is a technique that measures how many executable statements in a source code are executed by a test suite. Statement coverage is not appropriate for testing the price computation, as it does not consider the input data or output results. Equivalence partitioning is not state transition testing, which is a technique that models how a system transitions from one state to another depending on events or conditions. State transition testing is not relevant for testing the price computation, as it does not involve any states or transitions. Equivalence partitioning is not use case testing, which is a technique that tests how users interact with a system to achieve a specific goal. Use case testing is not applicable for testing the price computation, as it does not focus on a single function or component. Verified References: [A Study Guide to the ISTQB® Foundation Level 2018 Syllabus - Springer], Chapter 4, page 37-38.

Regression testing is a type of testing that verifies that previously tested software still performs correctly after changes. Regression testing can help prevent re-opening of defects fixed earlier by ensuring that they do not cause any new failures or side effects. The first recommendation to the company is to verify existing regression test suite are adequate, and augment it, if required, in order to ensure that defects fixed earlier get re-tested in each subsequent build. This can help improve the coverage and effectiveness of regression testing and detect any regression defects as soon as possible. Automating existing test suites may also help reduce the time and effort required for regression testing, but this is not the first recommendation, as automation may not be feasible or cost-effective for all test cases. Analyzing the product modules containing maximum defects and getting them thoroughly tested and defects fixed as a one-time activity may also help reduce the defect density and improve the quality of those modules, but this is not the first recommendation, as it does not address the root cause of re-opening defects fixed earlier. Training or replacing the teams responsible for development and testing of the modules containing maximum number of defects may also help improve their skills or performance, but this is not the first recommendation, as it may not be necessary or appropriate for all teams. Verified References: [A Study Guide to the ISTQB® Foundation Level 2018 Syllabus - Springer], Chapter 2, page 19; Chapter 4, page 45.

A failure is an event in which a component or system does not perform a required function within specified limits1. A requirement is a condition or capability needed by a user to solve a problem or achieve an objective2. In this case, the requirement is that the diagnostics tests should execute in less than 2 seconds. Therefore, any event that violates this requirement is a failure. The only option that clearly violates this requirement is B. The diagnostic tests take too much time to execute. If the diagnostic tests take more than 2 seconds to complete, then they do not meet the specified limit and thus fail. The other options are not necessarily failures related to the specified requirement. Option A. The diagnostic tests fail to start after a system reset is a failure, but not related to the time limit. It is related to the functionality of the self-diagnostics module. Option C. The diagnostic tests that measure the speed of the memory, fail is also a failure, but not related to the time limit. It is related to the accuracy of the memory tests. Option D. The diagnostic tests fail due to incorrect implementation of the test code is also a failure, but not related to the time limit. It is related to the quality of the test code. References = ISTQB® Certified Tester Foundation Level Syllabus v4.0, Requirements Engineering Fundamentals.

• The question is about marking the correct sentences among the given statements related to defects, failures, and mistakes. According to the ISTQB glossary, the definitions of these terms are1:
• Therefore, out of the five given statements, only two are correct, namely:
• The other three statements are incorrect, namely:

References:

• 1: ISTQB Glossary of Testing Terms 4.0, 2023, available at ISTQB) and ASTQB).

According to the decision table in the image, a Preferred Guest Card holder with a Silver room is eligible for an upgrade to Gold Luxury (YES), while a non-Preferred Guest Card holder, regardless of room type, is not eligible for any upgrade (NO). Therefore, Customer A (a Preferred Guest Card holder with a Silver room) would be offered an upgrade to Gold Luxury, and Customer B (a non-Preferred Guest Card holder with a Platinum room) would not be offered any upgrade. References = The answer is derived directly from the decision table provided in the image; specific ISTQB Certified Tester Foundation Level (CTFL) v4.0 documents are not referenced.

 Static testing is a form of testing that does not involve executing the software or system under test. It includes activities such as reviews, inspections, walkthroughs, and analysis of documents, code, and models. Static testing can find defects early in the development process, before they become more expensive and difficult to fix in later stages. Static testing can also improve the quality of the software or system by preventing defects from being introduced in the first place. Static testing can complement dynamic testing, which involves executing the software or system under test and checking the results against expected outcomes. Dynamic testing can find defects that static testing may miss, such as performance, usability, or integration issues. However, dynamic testing alone is not sufficient to ensure quality, as it may not cover all possible scenarios, inputs, or paths. Therefore, a test manager who decides to skip static testing is making a wrong decision, as he or she is ignoring the benefits of static testing and relying solely on dynamic testing, which may not be effective or efficient enough to find and prevent defects. References = ISTQB Certified Tester Foundation Level Syllabus, Version 4.0, 2018, Section 2.1.1, page 14; ISTQB Glossary of Testing Terms, Version 4.0, 2018, page 36; ISTQB CTFL 4.0 - Sample Exam - Answers, Version 1.1, 2023, Question 3, page 9.