CTFL_Syll2018 Exam Dumps - ISTQB Certified Tester Foundation Level (Syllabus 2018)

The statement that does not describe how testing contributes to higher quality is “The testing of software demonstrates the absence of defects”. This statement is false because testing cannot prove that a software system is defect-free or has a certain level of quality because there might be some untested inputs or outputs that could reveal defects or failures. Testing can only provide information about the quality and risk level of a software system based on the observed behavior and results under certain conditions and assumptions. The other statements describe how testing contributes to higher quality by:

• Performing a review of the requirement specifications before implementing the system can enhance quality: This statement is true because reviewing the requirement specifications can help identify and prevent defects, ambiguities, inconsistencies, or incompleteness in the requirements before they are implemented in the system, which can save time and effort and improve customer satisfaction.
• Properly designed tests that pass reduce the level of risk in a system: This statement is true because passing tests can increase confidence that the system meets its requirements and expectations and provides value to the users and customers. Passing tests can also reduce the probability or impact of failures or defects in the system that could cause harm or loss.
• Software testing identifies defects, which can be used to improve development activities: This statement is true because identifying defects can help analyze and remove their causes and prevent them from recurring in future development activities. Identifying defects can also help improve development processes, methods, standards, tools, techniques, etc., by providing feedback and lessons learned.

You can find more information about how testing contributes to higher quality in [A Study Guide to the ISTQB® Foundation Level 2018 Syllabus], Chapter 1.

Test estimation is the process of predicting the effort, time, and resources required for testing a software system. Test estimation depends on several factors that influence the scope, complexity, and quality of testing. Some of these factors are:

• Characteristics of the product: This factor indicates how difficult or challenging it is to test the software system based on its size, functionality, reliability, usability, performance, security, etc.
• Characteristics of the development process: This factor indicates how well or poorly the software system is developed based on the development methodology, standards, tools, techniques, etc.
• Characteristics of the test process: This factor indicates how effective or efficient the testing process is based on the test strategy, plan, design, execution, evaluation, etc.
• Characteristics of the test team: This factor indicates how skilled or experienced the test team is based on their knowledge, competence, motivation, communication, collaboration, etc.

The outcome of testing of previous test cycle is not a factor on which test estimation is dependent upon because it does not affect the effort, time, or resources required for testing the current test cycle. Rather, it is an outcome or consequence of test estimation that can provide feedback and lessons learned for improving future test estimations. You can find more information about test estimation in Software Testing Foundations: A Study Guide for the Certified Tester Exam, Chapter 22.

The diagram lists various types of operating systems (LNX, W2K, WSP), databases (ORA, MSQ, SQL), and application servers (JBS, WSP) supported by the application under test. To test all possible combinations of these types, we need to multiply the number of options in each category. In this case, we have:

• 3 options for operating systems
• 3 options for databases
• 2 options for application servers

Therefore, we have 3 x 3 x 2 = 18 possible combinations to test.

However, if we look closely at the diagram, we can see that some combinations are not valid or feasible because they are not connected by lines. For example, we cannot test LNX with WSP as an application server because there is no line between them. Similarly, we cannot test W2K with JBS as an application server because there is no line between them. Therefore, we need to exclude these invalid combinations from our calculation.

If we count only the valid combinations that are connected by lines in the diagram, we get:

• 5 combinations for LNX (LNX-ORA-JBS, LNX-ORA-WSP, LNX-MSQ-JBS, LNX-MSQ-WSP, LNX-SQL-JBS)
• 5 combinations for W2K (W2K-ORA-WSP, W2K-MSQ-WSP, W2K-SQL-WSP)
• 5 combinations for WSP (WSP-ORA-JBS, WSP-ORA-WSP, WSP-MSQ-JBS, WSP-MSQ-WSP)

Therefore, we have 5 + 5 + 5 = 15 valid combinations to test.

You can find more information about testing combinations in Software Testing Foundations: A Study Guide for the Certified Tester Exam, Chapter 4, Section 4.22.

Regression testing is a type of testing that is performed after a software system has been changed or modified to verify that the changes have not introduced any new defects or adversely affected the existing functionality of the system. Regression testing can be performed when the software system undergoes different types of changes, such as:

• Corrective changes: Changes that fix defects or errors in the software system
• Adaptive changes: Changes that adapt the software system to new platforms or environments
• Perfective changes: Changes that improve the performance or usability of the software system
• Preventive changes: Changes that avoid potential problems or issues in the software system

In this case, the software system was re-deployed because the backend database was changed from one vendor to another, which is an example of an adaptive change. Therefore, the test manager decided to perform some functional tests on the re-deployed system to ensure that the change did not affect the functionality of the system. This is an example of regression testing.

The other types of testing mentioned in the question are not relevant for this scenario. For example:

• Non-functional testing: This type of testing verifies the non-functional aspects of the software system, such as reliability, performance, security, usability, etc.
• Structural testing: This type of testing verifies the internal structure or implementation of the software system, such as code, architecture, design, etc.
• Unit testing: This type of testing verifies individual components or units of software in isolation from other components or systems.

You can find more information about regression testing in [A Study Guide to the ISTQB® Foundation Level 2018 Syllabus], Chapter 2, Section 2.4.

Use case testing is a specification-based test technique that is based on the use cases or scenarios that describe how users interact with the system under test. Use case testing aims to find defects in the process flow or functionality of the system under test by verifying that it behaves as expected according to the use cases or scenarios. Use case testing does not require any knowledge of the data flow or structure of the system under test; it only focuses on what the system does rather than how it does it. Use case testing can be done by professional testers or real users, depending on the level and purpose of testing. Use case testing can also be designed by customers or end users, developers, testers, analysts, or anyone who has access to the use case specifications or user requirements. You can find more information about use case testing in [A Study Guide to the ISTQB® Foundation Level 2018 Syllabus], Chapter 4, Section 4.2.

Memory leaks are errors that occur when a program does not release memory that it has allocated, causing the system to run out of memory and slow down or crash. Memory leaks cannot be detected by structure-based testing techniques, which are based on the code structure and logic. Structure-based testing techniques can only find errors that are related to the control flow, data flow, or logic of the program. For example, they can find errors such as features that are only partially implemented, data structures that are used before initialization, or division by zero. To detect memory leaks, you need dynamic analysis tools that monitor the memory usage of the program during execution. You can find more information about structure-based testing techniques and dynamic analysis tools in A Study Guide to the ISTQB® Foundation Level 2018 Syllabus, Chapter 4, Sections 4.2 and 4.31.

Risk-based testing is an approach to testing that prioritizes and focuses on testing activities based on the level of risk associated with each feature or function of the system under test. Risk-based testing aims to optimize the use of time, resources, and techniques for testing by identifying and addressing the most critical and likely sources of failure or harm in the system under test. Some examples of typical risk-based testing activities are:

• Brainstorming sessions are held with a wide variety of stakeholders to identify possible failures in the system: This activity is part of the risk identification process, which involves gathering information and opinions from different perspectives and sources to discover potential risks in the system under test.
• Tests are prioritized to ensure that those associated with critical parts of the system are executed earlier: This activity is part of the risk analysis and evaluation process, which involves assessing the probability and impact of each risk and ranking them according to their severity and importance.
• The focus of testing is shifted to an area in the system where tests find more defects than expected: This activity is part of the risk mitigation and monitoring process, which involves taking actions to reduce or eliminate the risks and tracking their status and progress.

The evaluation of a risk-management tool to decide which tool to use for future projects is not an example of a typical risk-based testing activity because it is not directly related to testing the system under test based on its risks. Rather, it is an example of a tool selection or evaluation activity, which involves comparing and choosing a tool that can support or enhance the testing process based on criteria such as functionality, usability, reliability, compatibility, cost, etc. You can find more information about risk-based testing in [A Study Guide to the ISTQB® Foundation Level 2018 Syllabus], Chapter 3, Section 3.4.

A decision table is a specification-based test technique that involves creating a table that shows the combinations of inputs and outputs for a system under test based on certain conditions and rules. A decision table can be used to design test cases that cover all possible scenarios and outcomes for a system under test. Some statements about decision tables are:

• I. Generally, decision tables are generated for low risk test items: This statement is false because decision tables can be generated for any level of risk test items depending on the complexity and variability of the system under test. Decision tables are especially useful for testing systems that have many inputs, outputs, conditions, and rules that affect their behavior or performance.
• II. Test cases derived from decision tables can be used for component tests: This statement is true because decision tables can be used to design test cases for any level or type of testing, including component tests. Component tests are tests that verify individual components or units of software in isolation from other components or systems.
• III. Several test cases can be selected for each column of the decision table: This statement is true because each column of the decision table represents a unique combination of inputs and outputs for the system under test based on certain conditions and rules. Therefore, each column can be used as a basis for selecting one or more test cases that cover that combination.
• IV. The conditions in the decision table represent negative tests generally: This statement is false because the conditions in the decision table can represent both positive and negative tests depending on the requirements and expectations of the system under test. Positive tests are tests that verify that the system under test behaves as expected under valid or normal inputs or conditions. Negative tests are tests that verify that the system under test handles errors or exceptions gracefully under invalid or abnormal inputs or conditions.

You can find more information about decision tables in [A Study Guide to the ISTQB® Foundation Level 2018 Syllabus], Chapter 4, Section 4.2.