ISTQB CTFL-2018 Practice Test - Questions Answers, Page 6

Maintenance testing is a type of testing that is performed after a software product has been delivered and deployed to ensure that it still meets its requirements and functions correctly after changes have been made to it or to its environment. Changes can include corrective changes (fixing defects), adaptive changes (adapting to new platforms or environments), perfective changes (improving performance or usability), or preventive changes (avoiding potential problems). One of the appropriate reasons for maintenance testing is to verify that the software product works as expected after upgrading the operating system, which is an example of an adaptive change. Other reasons for maintenance testing can include verifying that the software product works as expected after fixing defects, adding new features, improving performance, or preventing future issues. You can find more information about maintenance testing inSoftware Testing Foundations: A Study Guide for the Certified Tester Exam, Chapter 12.

Confirmation testing, also known as re-testing, is the process of testing a defect that has been fixed to verify that it has been resolved and does not affect other parts of the system. Confirmation testing is usually done by the same tester who reported the defect and using the same test case that revealed the defect. You can find more information about confirmation testing inA Study Guide to the ISTQB Foundation Level 2018 Syllabus, Chapter 3, Section 3.21.

System integration testing and acceptance testing are two different levels of testing that have different objectives and stakeholders. System integration testing is the process of testing the interactions and interfaces between different components or systems that form a larger system. System integration testing verifies that the system meets its functional and non-functional requirements and works as expected in its intended environment. System integration testing is usually done by testers or developers who have access to the system architecture and design specifications. Acceptance testing is the process of testing the system by the end users or customers to determine if it satisfies their needs and expectations and is ready for deployment or delivery. Acceptance testing verifies that the system complies with the user requirements and business processes and provides value to the stakeholders. Acceptance testing is usually done by users or customers who have access to the user requirements and business scenarios. You can find more information about system integration testing and acceptance testing inA Study Guide to the ISTQB Foundation Level 2018 Syllabus, Chapter 2, Sections 2.2 and 2.31.

Test metrics are quantitative measures that are used to monitor, control, and improve the test process and its outcomes. Test metrics can be collected at different levels of testing (test case, test suite, test project, etc.) and can be used for different purposes (planning, estimation, execution, evaluation, etc.). Some examples of common test metrics are:

Percentage of work done in test environment creation: This metric indicates how much effort has been spent on setting up and maintaining the test environment, which includes hardware, software, network, data, tools, etc., that are required for conducting the test activities.

Number of test cases run: This metric indicates how many test cases have been executed during a given period or phase of testing.

Deviation from test milestone dates: This metric indicates how much delay or ahead of schedule the test activities are compared to the planned dates.

Defect density: This metric indicates how many defects have been found per unit of size or functionality of the system under test.

Average number of expected defects per requirement is not a common test metric because it is not easy to estimate or measure how many defects are likely to be found for each requirement. Moreover, this metric does not provide useful information for improving the test process or evaluating the test results. You can find more information about test metrics inA Study Guide to the ISTQB Foundation Level 2018 Syllabus, Chapter 5, Section 5.41.

The extent of testing required for a software product or feature depends on several factors that influence the level of quality and risk involved in delivering or deploying it. Some of these factors are:

Budget to do testing: This factor indicates how much money is available or allocated for conducting the test activities, which affects the scope, depth, duration, and resources of testing.

Time available to do testing: This factor indicates how much time is available or allocated for conducting the test activities, which affects the schedule, frequency, speed, and coverage of testing.

Level of risk of the product or feature: This factor indicates how much impact or harm a failure or defect in the product or feature can cause to the users, customers, stakeholders, or environment, which affects the priority, intensity, complexity, and rigor of testing.

Complexity of the product or feature: This factor indicates how difficult or challenging it is to understand, design, implement, or maintain the product or feature, which affects the effort, skill, technique, and tool required for testing.

A particular tester involved in testing is not a deciding factor in determining the extent of testing required because it does not affect the quality or risk level of the product or feature being tested. Rather, it is an outcome or consequence of deciding how much testing is needed based on other factors such as budget, time, risk, and complexity. You can find more information about determining the extent of testing inSoftware Testing Foundations: A Study Guide for the Certified Tester Exam, Chapter 2, Section 2.12.

The term 'Pesticide paradox' refers to the phenomenon where the effectiveness of test cases that are repeated and focused on the same scenarios decreases over time because they tend to find the same defects or no defects at all. This is because the system under test becomes more resistant or immune to the existing test cases, just like pests become more resistant or immune to pesticides over time. To overcome the pesticide paradox, test cases should be regularly reviewed and updated to cover new or changed requirements, scenarios, risks, or defects. Test cases should also be designed to cover different aspects and perspectives of the system under test, such as functionality, usability, performance, security, etc. You can find more information about the pesticide paradox inA Study Guide to the ISTQB Foundation Level 2018 Syllabus, Chapter 4, Section 4.11.

Test techniques are methods or procedures that can be used to design, execute, or evaluate test cases. Test techniques can be classified into two categories: specification-based and structure-based. Specification-based test techniques, also known as black-box test techniques, are based on the requirements, specifications, or expectations of the system under test. They do not require any knowledge of the internal structure or implementation of the system. Some examples of specification-based test techniques are use case testing, state transition testing, decision table testing, etc. Structure-based test techniques, also known as white-box test techniques, are based on the code, architecture, or design of the system under test. They require some knowledge of the internal structure or implementation of the system. Some examples of structure-based test techniques are control flow testing, data flow testing, branch testing, statement testing, etc. You can find more information about test techniques inA Study Guide to the ISTQB Foundation Level 2018 Syllabus, Chapter 41.

Component testing is a part of the V-Model, which is a development life cycle model that shows the relationship between each phase of development and its corresponding phase of testing. In this model, each level of testing (unit testing, integration testing, system testing, acceptance testing) has a corresponding level of development (component design, component integration, system design, requirements analysis). Component testing is the process of testing individual components or units of software in isolation from other components or systems. Component testing verifies that the components meet their functional and non-functional requirements and work as expected in their intended environment. Component testing is usually done by developers who have access to the component design and code specifications. You can find more information about component testing and the V-Model inSoftware Testing Foundations: A Study Guide for the Certified Tester Exam, Chapter 22.

Pair programming is a software development technique where two programmers work together on the same code at the same workstation. One programmer, called the driver, writes the code while the other programmer, called the navigator, reviews the code and provides feedback and suggestions. Pair programming is not only a coding technique but also an informal review method because it involves constant communication and collaboration between the programmers who check each other's work and share their knowledge and skills. Pair programming can improve the quality and productivity of software development by reducing defects, increasing code readability, enhancing learning opportunities, and fostering creativity and innovation. Pair programming is usually used in agile methods such as Extreme Programming (XP), Scrum, or Kanban. It is not an alternative term for code inspection, which is a formal review method where a group of reviewers examine a piece of code in a structured and systematic way following predefined rules and roles. It is also not done with developer and tester pairing together because pair programming requires both programmers to have similar levels of expertise and familiarity with the code they are working on. You can find more information about pair programming inA Study Guide to the ISTQB Foundation Level 2018 Syllabus, Chapter 31.