ISTQB CTFL-Foundation - ISTQB Certified Tester Foundation Level

The Black-box testing technique is a method where the internal structure or workings of the item being tested are not known to the tester. This technique focuses on the input and output of the software system, ensuring that it meets the specified requirements without considering the internal code structure. It contrasts with White-box testing, which involves testing internal structures or workings of an application.

Determining whether enough testing has been performed involves considering several factors. These include:

(i) The exit criteria, which define the conditions that must be met to conclude testing. (ii) The budget, which affects the extent of testing that can be conducted. (iv) The product's risk profile,which helps prioritize testing efforts on high-risk areas. (vi) Sufficient details of the system status to allow decisions, ensuring that stakeholders have the necessary information to make informed decisions about the software's readiness.

These factors together ensure a balanced and informed decision-making process regarding the sufficiency of testing​​.

The application failed due to a defect in the purchase identification module. This defect could have been caused by a programmer mistake or an error in the specification. The incorrect counting of purchase attempts indicates a flaw in the logic or implementation of the module responsible for identifying successful purchases.

Component testing, also known as unit testing, involves testing individual components of the software separately. This type of testing focuses on the functionality of a specific section of the code. To facilitate this process, stubs and drivers are often used. Stubs are dummy modules that simulate the behavior of lower-level modules that are not yet integrated. Drivers are used to simulate higher-level modules that control the component being tested.

For a safety-critical system, it is essential to ensure that regression tests are run and passed following defect corrections at all test levels. Additionally, tracking incidents raised and closed at all levels of testing helps ensure that all defects are addressed and the system meets safety standards. These metrics provide a comprehensive view of both the completeness of testing and the effectiveness of defect resolution.

The failure rate in testing already completed is a useful metric to monitor progress along with test preparation and execution. It provides insight into the effectiveness of the tests and the quality of the product, helping to identify areas that may require additional attention or resources.

Static analysis is a technique used to find defects in software source code and software models without executing the code. It involves reviewing the code or models to identify potential issues, such as syntax errors, logical errors, or security vulnerabilities. Static analysis helps improve code quality and maintainability by catching defects early in the development process​​.

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In formal reviews, such as inspections, the role of the moderator is crucial. The moderator is responsible for leading the review process, ensuring that the review is conducted according to the defined procedures, and facilitating the review meeting. The ISTQB syllabus highlights that the moderator's role is to guide the review team, manage any issues that arise during the review, and ensure that the objectives of the review are met​​.

Static analysis tools are designed to examine the code without executing it. They are particularly effective at identifying structural issues in the code, such as potential infinite loops (B), which can occur due to incorrect logic that would cause the code to execute indefinitely. These tools analyze the code's structure and logic flow to find such issues early in the development process, helping to improve the code's quality before it is run​​.

When evaluating risks, both the likelihood of failure and the potential cost of impact must be considered. The risk with the highest level is determined by the product of these two factors. In this case, a 10% likelihood of failure with a potential cost of impact of $500,000 results in a higher risk (expected impact) compared to the other options. The expected impact is calculated as likelihood multiplied by impact, which is higher for option B​​.

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