Free ISTQB ISTQB-CTFL Practice Exam with Questions & Answers | Set: 12

The key difference between the mindsets for test activities and development activities lies in the objectives: a tester is primarily concerned with finding defects to ensure product quality, while a developer focuses on designing and building solutions. This distinct focus helps ensure thorough quality checks and balances within the software development life cycle​ (ISTQB not-for-profit association)​.

Comprehensive and Detailed In-Depth Explanation:

The Moderator (D) plays a key role in formal reviews by facilitating discussions, ensuring that reviews stay on track, and creating an open environment for feedback. The Manager (A) is responsible for overseeing the testing process but does not directly facilitate reviews. The Reviewer (B) is responsible for examining the work product, while the Review Leader (C) organizes reviews but does not necessarily mediate them.

 If a program got 100% decision coverage in a test, then it is guaranteed that every executable statement is covered. Decision coverage (also known as branch coverage) is a type of structural coverage (also known as white-box coverage) that measures how many decision outcomes have been exercised by a test suite. A decision outcome is a possible result of a decision point (such as an if-then-else statement) in a program’s code. Decision coverage requires that each decision point has both true and false outcomes executed at least once by a test suite. Decision coverage implies statement coverage, which is another type of structural coverage that measures how many executable statements have been executed by a test suite. Statement coverage requires that each executable statement is executed at least once by a test suite. Therefore, if a program got 100% decision coverage in a test, then it also got 100% statement coverage in a test, which means that every executable statement is covered. The other options are not guaranteed to be true if a program got 100% decision coverage in a test. Every output equivalence class has been tested and every input equivalence class has been tested are not guaranteed to be true if a program got 100% decision coverage in a test, because equivalence classes are based on functional requirements or specifications, not on code structure or logic. Equivalence classes are used in specification-based testing (also known as black-box testing), which is a type of testing that does not consider the internal structure or implementation of the system under test. Decision coverage is used in structure-based testing (also known as white-box testing), which is a type of testing that considers the internal structure or implementation of the system under test. Therefore, achieving 100% decision coverage does not imply achieving 100% equivalence class coverage. The “dead” code has not been covered is not guaranteed to be true if a program got 100% decision coverage in a test, because dead code (also known as unreachable code) is code that can never be executed due to logical errors or design flaws. Dead code can reduce readability and maintainability of the code, as well as increase complexity and size. Decision coverage does not account for dead code, as it only considers the decision outcomes that are possible to execute. Therefore, achieving 100% decision coverage does not imply that the dead code has not been covered. Verified References: A Study Guide to the ISTQB® Foundation Level 2018 Syllabus - Springer, page 36.

Acceptance criteria for user stories often include detailed specifications about data definitions, such as the format, allowed values, and default values for a data item. This helps ensure that the developed feature meets the expected requirements and provides a clear understanding for both developers and testers on what needs to be validated. Therefore, statement B is true as per the ISTQB CTFL syllabus​​.

Static analysis involves analyzing the software's code, design, and structure without executing the program. It can uncover various types of defects, including security vulnerabilities (II) and non-conformance to specifications and standards (III). However, static analysis cannot replace dynamic testing (I), which involves executing the software to observe its behavior under various conditions. Dynamic testing can identify failures that static analysis cannot, such as those related to runtime issues and interaction between different parts of the software. Statement IV is false because static analysis does not detect failures; it detects defects. Failures are observed when the software is executed, which is beyond the scope of static analysis.

An oracle is a mechanism or source that can provide the expected result for a given test input or situation. Sometimes old version of a product can be used as an oracle, if it is assumed that the old version behaves correctly for the test cases that are executed on the new version. This is also known as back-to-back testing. Oracles do not help in reproducing the irreproducible bugs, as they only provide the expected results, not the actual results. Oracles are not derived from the design, but from the requirements or specifications. Oracles cannot be generated automatically using data generators, as data generators only provide test inputs, not test outputs. Verified References: A Study Guide to the ISTQB® Foundation Level 2018 Syllabus - Springer, page 9.

The support offered by a performance testing tool is often leveraged by testers to run load tests, which are tests that simulate a large number of concurrent users or transactions on the system under test, in order to measure its performance, reliability, and scalability. Performance testing tools can help testers to generate realistic workloads, monitor system behavior, collect and analyze performance metrics, and identify performance bottlenecks. The other statements are false, because:

A test data preparation tool is a tool that helps testers to create, manage, and manipulate test data, which are the inputs and outputs of test cases. Test data preparation tools are not directly related to running automated regression test suites, which are test suites that verify that the system still works as expected after changes or modifications. Regression test suites are usually executed by test execution tools, which are tools that can automatically run test cases and compare actual results with expected results.

A bug prediction tool is a tool that uses machine learning or statistical techniques to predict the likelihood of defects in a software system, based on various factors such as code complexity, code churn, code coverage, code smells, etc. Bug prediction tools are not used by testers to track the bugs they found, which are the actual defects that have been detected and reported during testing. Bugs are usually tracked by defect management tools, which are tools that help testers to record, monitor, analyze, and resolve defects.

A continuous integration tool is a tool that enables the integration of code changes from multiple developers into a shared repository, and the execution of automated builds and tests, in order to ensure the quality and consistency of the software system. Continuous integration tools are not used by testers to automatically generate test cases from a model, which are test cases that are derived from a representation of the system under test, such as a state diagram, a decision table, a use case, etc. Test cases can be automatically generated by test design tools, which are tools that support the implementation and maintenance of test cases, based on test design specifications or test models. References: ISTQB Certified Tester Foundation Level (CTFL) v4.0 sources and documents:

ISTQB® Certified Tester Foundation Level Syllabus v4.0, Chapter 3.4.1, Types of Test Tools

ISTQB® Glossary of Testing Terms v4.0, Performance Testing Tool, Test Data Preparation Tool, Bug Prediction Tool, Continuous Integration Tool, Test Execution Tool, Defect Management Tool, Test Design Tool

Debugging the software to find the reason for defects is not a common objective of testing, but rather a task of development or maintenance. Debugging is a process of locating and fixing errors in the software code, while testing is a process of finding and reporting defects in the software behavior or quality. Testing does not aim to fix defects, but rather to provide information on their existence and impact. The other options are common objectives of testing. Finding defects in the software is one of the main objectives of testing, as it helps to improve the quality and reliability of the software. Preventing defects is another objective of testing, as it helps to avoid rework and reduce costs and risks. Providing information on the status of the system is another objective of testing, as it helps to support decision making and risk management. Verified References: A Study Guide to the ISTQB® Foundation Level 2018 Syllabus - Springer, page 3.