Foundation Level ISTQB-CTFL Syllabus Exam Questions Answers

Risk level is determined by the combination of two factors: the likelihood of an event occurring and the impact or harm that could result from that event. This approach allows risks to be prioritized based on their potential effect on the project or system. The likelihood represents the probability of the risk event occurring, while the impact represents the severity of the consequences if the event does happen. This concept is fundamental in risk-based testing and helps guide decision-making during the testing process.References:

ISTQB Certified Tester Foundation Level Syllabus v4.0, Section 1.4.1.

A decision table is a technique that 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). The following statements about decision tables are true:

II. Test cases derived from decision tables can be used for component tests. Decision tables can be used to test components that have multiple inputs and outputs that depend on logical combinations of conditions. Decision tables can help cover all possible combinations or scenarios in a systematic way.

III. Several test cases can be selected for each column of the decision table. A column of a decision table represents a unique combination of condition entries and action entries. Several test cases can be selected for each column by varying other input values or expected results that are not part of the decision table. The following statements about decision tables are false:

I. Generally, decision tables are generated for low risk test items. Decision tables are not related to risk level, but rather to complexity level. Decision tables are generated for test items that have complex logic or multiple conditions and actions that need to be tested.

IV. The conditions in the decision table represent negative tests generally. The conditions in the decision table represent both positive and negative tests, depending on whether they are valid or invalid inputs for the test item. Verified References: A Study Guide to the ISTQB® Foundation Level 2018 Syllabus - Springer, Chapter 4, page 42-43.

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.

The whole team approach involves collaboration among all team members, including testers, developers, and business representatives, to achieve quality goals. However, this approach may not be suitable in situations where a high level of test independence is required. Test independence is essential in cases where unbiased testing is critical, such as in regulated environments or where high-risk systems are involved. This is because team members might unintentionally influence each other's work, leading to potential bias in testing outcomes​​.