ISTQB CTFL-2018 Practice Test Questions, Exam Dumps

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CTFL-2018 ISTQB Practice Test Questions and Exam Dumps

Question No 1:

Which of the following best defines what a test case is?

A. A statement about what to test in terms of measurable coverage criteria from analysis of the test basis.
B. A set of preconditions, inputs, actions, expected results and postconditions developed based on test conditions.
C. A description of the test objectives to be achieved and the means and the schedule for achieving them.
D. A source to determine expected results to compare with the actual result of the system under test.

Answer: B

Explanation:

A test case is a fundamental unit of testing used in software quality assurance. It is a specific set of conditions under which a tester will determine whether an application, software system, or one of its features is working as expected. The best and most comprehensive definition of a test case is found in option B, which states that it is “a set of preconditions, inputs, actions, expected results and postconditions developed based on test conditions.” This reflects the standard format and components that comprise a complete test case, making B the most accurate and complete choice.

Let’s evaluate each option carefully to explain why B is the most appropriate and why the others fall short:

Option A refers to what are typically known as test conditions. These are abstract ideas derived from analysis of the test basis—such as specifications, use cases, or requirements—and they guide the tester on what to cover. Test conditions are high-level and do not include the specific details necessary to execute a test. They are useful for planning but not for execution. Hence, A does not accurately describe a test case.

Option C refers more closely to a test plan or test strategy, not a test case. A test plan outlines the scope, objectives, schedule, resources, and activities needed for testing. It defines how the testing will be conducted but does not include specific actions or inputs like a test case does. Therefore, while it’s an important document in the testing process, it is not equivalent to a test case, making C an incorrect choice.

Option D is closer to the definition of a test oracle. A test oracle is the mechanism by which testers determine whether a test has passed or failed—essentially, it provides the expected results against which actual outcomes are compared. While a test case may include expected results (often derived from a test oracle), the test oracle itself is not a test case. As a result, D is incorrect.

In contrast, Option B captures all the critical elements necessary for test execution: what needs to happen before the test (preconditions), what inputs will be provided, what actions will be taken during the test, what the expected outcome should be, and what the state should be after the test (postconditions). This level of detail allows testers to perform the test and evaluate its success or failure accurately and consistently.

Thus, B provides the most complete, accurate, and practical definition of a test case, which is why it is the correct answer.

Question No 2:

In the context of software development, testing and debugging are critical activities that support software quality.

Which of the following actions are considered part of DEBUGGING, rather than testing?

A a and d
B a and b
C b and c
D c and d

Correct Answer: C

Explanation:

To determine which activities belong to debugging rather than testing, it’s important to understand the distinction between these two terms. Testing is primarily focused on detecting defects—it's the process of executing a program with the intent of finding errors or verifying expected behavior. Debugging, on the other hand, begins after a failure has been observed during testing or production. Debugging is the activity of investigating the underlying cause of that failure and correcting it.

Let’s evaluate each of the four options in the context of this definition.

Option a refers to designing tests to find failures. This is clearly a testing activity, not debugging. It’s done in the planning and preparation phase of testing to anticipate potential weak points in the software and to validate its behavior. The aim is to expose faults, not to fix them. Therefore, this is not a debugging activity.

Option b involves locating the cause of failures. This is a core debugging task. After a failure is detected during testing, developers engage in debugging to trace the failure back to its root cause in the source code, logic, or design. This is an investigative process that may require tools like debuggers, logs, or even manual code inspection.

Option c is about analyzing and fixing the defects. This is another core debugging responsibility. Once the cause of a defect is understood, developers take corrective action to remove the bug and ensure the system behaves as intended. This step directly follows the root cause analysis and is essential to restoring or improving the software’s quality.

Option d involves executing tests to show failures. Like option a, this is part of testing, not debugging. The goal here is to run test cases against the system and observe whether it behaves correctly or fails. It does not involve analyzing why a failure occurred or correcting the underlying problem, which are hallmarks of debugging.

To summarize:

a and d are testing activities.
b and c are debugging activities.

Therefore, the correct answer is C, as it includes both of the activities that are truly part of debugging. Understanding the division between testing and debugging is essential in the software development lifecycle, as it ensures responsibilities are correctly assigned and that teams focus their efforts efficiently. While testing helps detect problems, debugging is what actually leads to resolving them. A comprehensive approach to quality assurance will always include both, but they serve distinct and complementary purposes.

Question No 3:

Which of the following options accurately represents the correct sequence in the chain of events in software engineering, starting from the initial human action?

A. Error, fault, failure
B. Fault, bug, mistake
C. Mistake, failure, fault
D. Failure, bug, error

Answer: A

Explanation:

In software engineering, the sequence error → fault → failure is widely accepted as the proper representation of how problems propagate within a system. This sequence begins with a human mistake, referred to as an error, which is an incorrect action or decision made during activities such as coding, designing, or requirements gathering. This human error introduces a fault into the software—often known as a bug—which is a flaw or defect in the code or system that can cause it to operate incorrectly. When the faulty code is executed, it may cause the system to behave in an unintended way, resulting in a failure, which is an observable deviation from the expected behavior of the system.

Let’s analyze the provided options:

A. This is the correct answer. The chain starts with an error, which is a human mistake. This leads to a fault in the system (a defect or bug in the code). When the faulty code executes, it causes a failure in the system. This is the correct chronological order that represents the flow from cause (human action) to effect (system malfunction).
B. This option incorrectly sequences the terms. A fault cannot precede a bug, since they are essentially synonyms in many contexts, and a mistake (which aligns with the concept of an error) is the initial cause, not the final one. Additionally, this sequence lacks a clear distinction of the transition from human error to system-level failure.
C. This starts with a mistake, which is appropriate, but follows it with failure, and then fault. This reverses the correct cause-effect relationship. A fault must exist before a failure can occur. The presence of a fault might not always result in a failure unless certain conditions are met during execution. Therefore, this sequence is incorrect.
D. This sequence begins with failure, which is the end result, not the starting point. Placing failure first contradicts the chronological nature of the chain. Following that with bug and error further reverses the proper order of events. The root cause of a failure is usually an error, not the other way around.

Thus, the accurate and standard sequence in software reliability and engineering is error → fault → failure, which is reflected in option A. This model helps in tracing back a failure to its root cause and is fundamental in software testing, debugging, and quality assurance processes.

Question No 4:

A developer introduces a fault in the code while making a change to a software system. The fault is not detected during testing and is released into the live environment.

What is the guaranteed outcome of this mistake?

A The system will fail, causing a defect.
B If the defect is executed, the system may fail.
C Loss of money, time, or business reputation.
D Contractual requirements have not been met by testing.

Correct answer: B

Explanation:

This question focuses on the distinction between faults, defects, and failures within the software development and testing lifecycle. It evaluates your understanding of what happens when a coding error is introduced and not detected before the software is deployed.

In software terminology, a fault (also known as a bug or error) refers to an issue in the code that may potentially cause incorrect behavior. When this fault is triggered or executed during program operation, it can lead to a failure, which is an observed deviation from the expected behavior of the system. The fault becomes a defect when it resides in the code and has the potential to cause a failure. Importantly, a fault does not always result in a failure unless the part of the code containing the fault is executed under specific conditions that expose the problem.

Let’s analyze the options:

A states that “the system will fail, causing a defect.” This is incorrect because while the defect (or fault) exists in the code, the system will not necessarily fail unless that faulty code is actually executed. Not all faults lead to immediate or observable failures, especially if the conditions under which the fault would trigger are not met during typical use.

B is the correct answer because it correctly captures the conditional nature of software failures. If the code containing the defect is executed, then the system may fail. The failure is not guaranteed, but it becomes a possibility depending on the inputs, environment, and usage paths. This is consistent with standard definitions in software quality where a defect becomes a failure only upon execution in a way that exposes the problem.

C is a possible consequence, but not a definite one. While it's true that software issues can result in financial loss, wasted time, or reputational damage, this depends on the severity of the defect and how it impacts end users. Some defects might go unnoticed for long periods or have minimal impact.

D suggests that the contractual requirements of testing have been violated. However, even with well-designed testing processes, some defects can still escape detection. This does not necessarily mean that the testing failed to meet contractual obligations. It might indicate a need for improved testing strategies, but it’s not a definite outcome of the scenario presented.

Therefore, the only definite consequence in this situation is that there is now a defect in the live system, and if it is executed, it may result in a system failure. That makes B the most accurate and precise answer to the question.

Question No 5:

Which of the following options BEST explains the pesticide paradox principle of testing?

A If we do not regularly review and revise our tests, we’ll stop finding defects.
B Repeatedly running a set of tests will ensure that a system is defect free.
C Defects are, paradoxically, often contained in a small number of modules.
D Testing, like spraying pesticide, is an effective bug/defect removal activity.

Correct Answer: A

Explanation:

The pesticide paradox is a well-known principle in software testing, which draws a parallel between testing software and using pesticide on crops. Just as insects eventually develop resistance to the same pesticide if it is used repeatedly, software defects can go undetected if the same set of test cases is used over and over again. The idea is that the test cases will only catch the defects they are designed to find, and if no new test cases are introduced, new or previously undetected bugs will not be discovered. Hence, the tests lose their effectiveness over time unless they are regularly revised and updated to cover new paths, conditions, and scenarios.

Option A is the most accurate explanation of the pesticide paradox. It correctly identifies that if test cases are not periodically reviewed, revised, and enhanced, they will become less effective. In other words, existing test cases might stop identifying new defects simply because those specific paths in the code have already been tested and fixed. To uncover new defects, testers must think creatively and evolve their test suites to adapt to changes in the system and emerging risk areas.

Let’s analyze the other options to understand why they are incorrect:

B suggests that repeatedly running a set of tests ensures a system is defect-free. This is misleading because it contradicts the pesticide paradox. Running the same tests repeatedly might confirm that previously found defects remain fixed, but it does nothing to detect new defects or cover untested areas. Testing cannot guarantee a defect-free system; it can only reveal the presence of defects, not their absence.
C refers to the principle known as the Pareto principle or the 80/20 rule in testing, which states that approximately 80% of defects are found in 20% of the modules. While this is a valid concept in software quality, it is unrelated to the pesticide paradox and thus not the best explanation.
D suggests that testing is an effective bug-removal activity, which confuses testing with debugging. Testing is the process of identifying bugs, while debugging is the activity of fixing them. Moreover, this choice doesn't address the paradox element at all and instead focuses on an unrelated analogy.

In summary, the pesticide paradox underscores the importance of continually evolving the test suite to ensure its ongoing effectiveness. The best way to ensure defects continue to be discovered is to change and expand the tests to address new areas of risk. Therefore, the most accurate answer is A.

Question No 6:

During which stage of the fundamental test process is the testability of requirements evaluated?

A. Test Execution
B. Test Planning
C. Test Design
D. Test Analysis

Answer: D

Explanation:

The stage of the fundamental test process during which the testability of requirements is evaluated is the test analysis phase. This phase is crucial in the software testing lifecycle because it involves examining and interpreting the test basis—which includes the requirements, architecture, design specifications, and other relevant documentation—to determine what can be tested and how it should be approached. In this stage, testers assess whether the requirements are sufficiently clear, complete, and measurable to allow for meaningful test cases to be derived.

The term testability refers to how easily a requirement can be tested, and that usually hinges on whether it is specific, unambiguous, and verifiable. For example, a requirement stating "the application should be fast" is not testable because "fast" is subjective. However, a requirement like "the application should load the dashboard within 2 seconds under normal load conditions" is testable because it sets a measurable standard. During test analysis, testers evaluate all such requirements for clarity and feasibility, which directly ties into how effective and meaningful the testing will be. If requirements are found to be non-testable, feedback is typically given to the requirements engineers or stakeholders to improve them before proceeding to the next steps.

To clarify the other options:

A. Test Execution: This is the phase where actual test cases are run on the system under test. Any problems with testability discovered during this stage are usually too late to correct without delaying the testing process. Execution is focused on applying what has already been planned and designed, not on evaluating requirements.
B. Test Planning: During test planning, the focus is on defining the objectives, scope, approach, and resources required for testing. While some high-level reviews may be done, detailed evaluation of the testability of individual requirements is not the primary goal here.
C. Test Design: In the test design phase, testers transform test conditions and scenarios into test cases and scripts. The assumption in this stage is that the requirements have already been evaluated for testability, so the focus is on creating the actual tests, not on determining whether the requirements themselves are testable.

Therefore, test analysis is the stage where testability is directly evaluated and ensures that testing can be carried out in a structured and effective way based on well-understood, measurable requirements. This evaluation is essential because it influences the quality of the entire testing process, from planning through to execution. If the requirements are not testable, it compromises the entire foundation upon which the tests are built. Hence, identifying and resolving testability issues during test analysis is a vital quality assurance step.

Question No 7:

Which of the following would achieve the HIGHEST level of testing independence for a project's system test level?

A Training developers to design good tests for the test team to execute.
B Outsourcing test design and execution to a different company.
C Having the company’s independent test team design and execute the tests.
D Minimising contact between testers and developers during test design to avoid bias.

Correct answer: B

Explanation:

Testing independence refers to the degree of separation between the people who develop a system and the people who test it. The main idea is that independent testers are more likely to view the system objectively and find defects that developers may overlook due to their familiarity or assumptions. The higher the level of independence, the more impartial and effective the testing effort can be.

Option A, which involves training developers to design good tests for the test team to execute, does offer some degree of improvement in test quality, but the tests are still influenced by the developers’ perspective. Even if the execution is handled separately, the design of the tests is not fully independent.

Option C, having the company's independent test team design and execute the tests, reflects a common and effective structure in many organizations. Internal independence can be beneficial and usually provides more objectivity than relying on developers. However, this team still operates within the same corporate structure and may be subject to internal pressures, biases, or organizational culture that can impact complete impartiality.

Option D, which focuses on minimizing contact between testers and developers, is more of a procedural safeguard to reduce bias. While helpful, this method alone does not provide structural or organizational independence. It may reduce influence but doesn't ensure testers are completely separate in terms of responsibilities or reporting structure.

Option B offers the highest level of testing independence. Outsourcing test design and execution to an external company removes any organizational or internal project influence. The outsourced team is not part of the development organization, so they are less likely to be influenced by internal politics, assumptions, or pressures. External testers rely solely on documentation, requirements, and specifications, which enforces an objective approach to testing. While this level of independence comes with its own challenges—such as communication gaps, increased costs, and potential delays—it is the most structurally independent method available.

Therefore, considering the goal of achieving the highest level of testing independence, B is the correct answer because it ensures the testers are completely external to the development process and organization, minimizing any form of bias or conflict of interest.

Question No 8:

What is the most effective method for leveraging the different mindsets of developers and testers in a software development environment?

A Insist on independent testing at all stages in the lifecycle
B Have all developers undergo ISTQB training
C Keep developers and testers in separate teams
D Bring the two mindsets together

Correct answer: D

Explanation:

One of the most important aspects of modern software development is understanding and appreciating the different perspectives that developers and testers bring to a project. Developers typically focus on building software that works—meeting specifications, implementing features, and optimizing performance. In contrast, testers are oriented toward discovering what doesn’t work—identifying edge cases, failures, inconsistencies, and usability issues. These distinct mindsets are not in conflict; rather, they are complementary, and leveraging them together effectively can greatly improve software quality and reduce delivery risks.

The correct answer is D because bringing the two mindsets together fosters collaboration, mutual understanding, and shared ownership of quality. This approach encourages early communication, continuous feedback, and joint problem-solving, especially in agile and DevOps environments where teams are cross-functional. By involving testers early in the development cycle, and encouraging developers to think about how their code will be tested, organizations can prevent defects rather than just detect them. Collaboration can also improve requirements clarity and reduce misunderstandings between teams.

Looking at the other options:

A, insisting on independent testing at all stages, emphasizes separation rather than collaboration. While independence can help maintain objectivity, strict independence throughout the lifecycle may create communication barriers and slow down the development process. Independent testing is beneficial in certain stages, such as user acceptance testing or regulatory reviews, but not necessarily at all stages. It should be balanced with collaborative testing strategies.

B, requiring all developers to undergo ISTQB training, is well-intentioned but insufficient as a standalone strategy. While this may help developers understand testing principles, it does not inherently foster collaboration or leverage the unique mindset of testers. Furthermore, ISTQB is designed primarily for testers; although useful, it’s not essential for every developer to have this specific certification to improve team dynamics.

C, keeping developers and testers in separate teams, reinforces siloed thinking. This may have been common in traditional waterfall models but is considered counterproductive in modern software engineering practices, where integration, continuous testing, and collaboration are key. Separation can lead to a lack of shared understanding and may delay the detection of issues until later in the development cycle.

In conclusion, D is the best approach because it emphasizes collaboration over isolation, integration over segregation, and communication over assumptions. By combining the developer's mindset of constructing software with the tester’s mindset of deconstructing it, teams can produce better, more reliable software faster and more efficiently.

Question No 9:

In which software development life cycle model does regression testing become increasingly important as the project advances?

A V-model
B Waterfall
C Scrum
D Progressive

Correct answer: C

Explanation:

The development life cycle model where regression testing becomes increasingly important as the project progresses is Scrum, which is an Agile methodology. Scrum is characterized by iterative and incremental development through sprints, which are time-boxed iterations where specific features are developed, tested, and potentially delivered. Each new sprint introduces new functionality, and with each addition, it is critical to ensure that previously developed and tested features continue to function correctly. This necessity makes regression testing a crucial and growing activity throughout the project's lifespan.

As the codebase evolves, the potential for new changes to inadvertently affect existing functionality grows. Therefore, each sprint typically includes regression tests that confirm the stability and reliability of existing features. This practice ensures that the integration of new code does not break existing functionality, a risk that increases with each iteration. Thus, the importance of regression testing naturally scales with the project.

Option A, the V-model, does incorporate regression testing, but it is primarily focused on a corresponding test phase for each development phase. While testing is integral to the model, it is more structured and linear, and regression testing is not uniquely emphasized as the project progresses in the same compounding manner seen in Scrum.

Option B, the Waterfall model, is a linear and sequential development process. Each phase is completed before the next begins, and although testing (including regression testing) occurs, it happens mainly after the coding phase. There is limited flexibility for iterative regression testing throughout the project since earlier phases are generally not revisited unless the entire cycle is restarted.

Option D, Progressive, is a vague or undefined term in the context of standard software development models. It may imply gradual or evolutionary development, but it is not recognized as a formal model like Scrum, Waterfall, or V-model. Without a specific methodology behind it, it doesn’t accurately fit the context of structured regression testing within project evolution.

Therefore, Scrum best fits the description, as it inherently promotes continuous testing, including regression testing, as an essential and expanding practice with each sprint. Agile teams often rely heavily on automated regression test suites to maintain software quality and stability while supporting frequent updates and deployments. As the product grows in complexity, these regression checks help ensure that newly introduced changes do not compromise existing functionality, underscoring why regression testing becomes increasingly critical in Scrum environments.

Question No 10:

Which of the following apply to System Testing?

A. a and c.
B. b and d.
C. a and b.
D. c and e.

Correct answer: C

Explanation:

System testing is a critical phase in the software testing life cycle that involves evaluating a completely integrated system to verify that it meets its specified requirements. It serves as the first level of testing where the entire application is tested as a whole, and it is primarily based on the system specifications or requirements documents. At this stage, both functional and non-functional aspects of the software are tested to ensure the product performs as expected in all relevant scenarios.

Let’s analyze the listed options one by one:

a) May satisfy legal requirements.
This is correct. System testing may involve validating regulatory and compliance requirements, especially in domains like finance, healthcare, and aviation, where legal standards must be met before the product is released. The process ensures that the software adheres to all applicable laws, standards, or guidelines. For instance, in medical software, failing to meet system-level requirements can result in regulatory penalties. System testing might check for compliance with regulations like HIPAA, GDPR, or ISO standards, depending on the domain.
b) Can use system specifications as a test basis.
This is also correct. System testing typically uses system requirement specifications (SRS) as a test basis. This includes functional requirements (what the system should do) and non-functional requirements (how the system should behave). Test cases are derived from these specifications to validate that the system meets all defined behaviors. For instance, if a requirement states that the system should support 1,000 concurrent users, a system test would verify whether this condition is met under specified performance criteria.
c) Often the responsibility of business users.
This is not correct in the context of system testing. System testing is typically conducted by independent QA or test teams, not by business users. Business users are more commonly involved in user acceptance testing (UAT), where they validate that the system meets business needs. UAT is the final validation before the product goes live and often involves real-world scenarios specific to the business context.
d) Main goal is to establish confidence.
While building confidence in the system is certainly a benefit of system testing, it is not the primary goal. The main objective is to verify the system against the specified requirements, ensuring everything works together as expected. Confidence building is more associated with acceptance testing, where stakeholders need to be reassured that the system fulfills their expectations and is ready for deployment.
e) Should focus on the communication between systems.
This is typically a concern for integration testing, which comes before system testing. Integration testing ensures that different modules or systems work together properly. System testing, by contrast, examines the entire system as a whole, including its behavior under various conditions, but it assumes the modules are already well-integrated.