Unit Testing Standards Quiz

Defects that are detected early are often much cheaper to remove because they can be addressed and fixed before they have a chance to cause further issues or impact other parts of the system. Early detection allows for quicker and more efficient resolution, reducing the time and effort required for debugging and rework. This helps to minimize the overall cost associated with defect removal and ensures that the product or system is delivered with higher quality and fewer issues.

The integration strategy refers to the approach used to combine different components or modules of a system. Top-down, bottom-up, and big-bang are all commonly used integration strategies. However, design-based is not a recognized integration strategy.

Boundary value analysis is a form of functional testing that focuses on testing the system's behavior at the boundaries of input values. It involves testing the minimum and maximum values, as well as values just above and below these boundaries, to ensure that the system handles them correctly. This type of testing helps identify issues related to boundary conditions, such as off-by-one errors or incorrect handling of edge cases. It is an effective technique for identifying defects and ensuring the system's functionality is robust.

Regression testing is likely to benefit most from the use of test tools providing test capture and replay facilities. Regression testing involves retesting previously tested functionality to ensure that changes or fixes have not introduced new defects. Test capture and replay tools allow testers to record and replay test scenarios, making it easier to repeat tests and compare results. This can significantly speed up the regression testing process and increase efficiency.

User requirements are the best source of expected outcomes for User Acceptance Test scripts because they outline the specific functionalities and features that the user expects from the system. These requirements serve as a baseline for determining whether the system meets the user's needs and expectations. Program specification and system specification may provide technical details and constraints, but they may not necessarily capture the user's perspective. Actual results, on the other hand, are the observed outcomes after executing the test scripts and cannot be used as a source for expected outcomes.

The benefits of using tools to support testing include greater consistency and repeatability, objective assessment, ease of access to information about tests or testing, and reduced repetitive work. These benefits help improve the efficiency and effectiveness of the testing process. However, there are also risks associated with using these tools, such as over-reliance on the tool, unrealistic expectations, and underestimating the effort required to maintain the test assets generated by the tool. These risks can lead to potential issues and limitations in the testing process.

Incident reports would not normally form part of a test plan because incident reports are typically used to document and track issues or problems that occur during testing or in production. They are not typically used to outline the overall strategy or approach for testing. A test plan typically includes features to be tested, risks, and the schedule for executing the tests.

Equivalence partitioning and boundary value analysis are closely related specification-based testing techniques. Equivalence partitioning involves dividing the input domain into different equivalence classes and selecting representative values from each class for testing. Boundary value analysis focuses on testing the boundaries and limits of the input domain, including values at the lower and upper bounds, as well as just inside and just outside those boundaries. Both techniques aim to identify and test the different possible scenarios and potential errors that may occur within the input domain of a system.

The correct answer is to analyze your needs and requirements. This is the most logical and practical step to take when looking for a new test tool. By analyzing your needs and requirements, you can determine what specific features and functionalities you require from a test tool. This will help you narrow down your options and choose a tool that best fits your needs. Attending a tool exhibition or inviting a vendor for a demo may be helpful later in the process, but it is important to first understand your own requirements before exploring external options. Searching the internet can also be useful, but it should be done after analyzing your needs to ensure you are searching for the right type of tool.

The valid equivalence class for the field on the student registration form is alphanumeric values, meaning it can accept both letters and numbers. The given answer "BoOkLeT ; B01kL0t" falls under this valid equivalence class as it contains a combination of uppercase and lowercase letters, as well as numbers.

Stress testing is not described in a unit test standard. Unit tests focus on testing individual units of code in isolation, typically at the function or method level, to ensure that they work correctly. Stress testing, on the other hand, is a type of testing that evaluates the system's performance and stability under extreme conditions, such as high loads or limited resources. While stress testing is important, it is typically not included in unit test standards as it goes beyond the scope of unit testing.

The reason why testing is split into distinct stages is because each stage serves a different purpose. By dividing testing into stages, it allows for a systematic approach where each stage focuses on specific aspects of testing, such as unit testing, integration testing, system testing, and user acceptance testing. This helps ensure that all necessary testing is conducted and allows for better organization and management of the testing process.

The requirement that states "The response time shall be less than one second for the specified design load" is testable because it can be measured and verified. It specifies a specific performance metric (response time) and a target value (less than one second) that can be objectively tested against the actual performance of the system under the specified design load.

The correct answer is I and III. This is because statement I states that regression tests can be automated if they are well designed, which implies that automation can be useful for regression tests. Statement III states that regression tests are a way to reduce the risk of a change having an adverse effect elsewhere in the system, which aligns with the purpose of regression testing. Therefore, both statements I and III are true.

The given answer states that explanations I, IV, and V are possible root causes for the high number of field failures, while explanations II and III are not possible. This suggests that not executing all the tests planned for the significant product risks, failing to identify all important risks from a customer point of view, and not updating the product risk analysis during the project as new information became available could be the reasons for the high number of field failures. However, having unrealistic expectations of the percentage of defects that testing can find and a version-control issue resulting in the release of a version of the software used during early testing are not considered possible root causes.

Verification early in the life cycle reduces defect multiplication. This means that by identifying and addressing defects early on, the likelihood of those defects causing further issues or multiplying into more complex problems is minimized. This is beneficial because it saves time and resources that would otherwise be spent on fixing and retesting these multiplied defects later in the project. By catching and resolving defects early, the overall quality of the product is improved and the risk of major issues occurring later in the development process is reduced.

The correct answer is I and III are primarily product risks, while II, IV and V are primarily project risks. This is because risk I is related to the incorrect calculation of fees, which is a product-related issue that can affect the organization. Risk III is about a defect that can allow hackers to gain administrative privileges, which is also a product-related risk. On the other hand, risks II, IV, and V are all related to the project itself, such as vendor delivery, skills gap, and defect prioritization process, which can impact the project's success.

The V-model is a software development model that emphasizes the verification and validation of designs. It includes the verification of designs because it follows a sequential process where each phase of development is associated with a corresponding testing phase. This means that the design phase is followed by the design verification phase, where the design is checked for accuracy and completeness. Therefore, the statement "It includes the verification of designs" is true for the V-model.

The main focus of acceptance testing is to test for a business perspective. This means that the testing process aims to ensure that the system meets the business requirements and objectives. It involves evaluating whether the system functions as intended and whether it is suitable for use in the specific business environment. Acceptance testing is typically performed by end-users or stakeholders to determine if the system is acceptable and ready for deployment. It is not primarily about finding faults in the system or testing it with other systems, although these aspects may be included in the overall testing process.

The minimum set of test input values to cover all valid equivalence partitions is 15, 19, and 25 degrees. This is because these values represent the lower limit, middle value, and upper limit of the valid equivalence partitions. A temperature below 18 degrees (15 degrees) triggers the heating to switch on, a temperature between 18 and 21 degrees (19 degrees) does not trigger any action, and a temperature above 21 degrees (25 degrees) triggers the heating to switch off. Therefore, testing these three values ensures that all possible scenarios are covered.

An acceptance test plan is a likely name for the document that describes a level of testing where the primary goal is establishing confidence in the system. This plan outlines the tests that will be conducted to determine whether the system meets the specified requirements and is ready for acceptance by the stakeholders. It typically includes details on the scope, objectives, test cases, and acceptance criteria for the testing phase.

The test principle that would better align with the test objective of finding as many defects as possible during system testing is Defect clustering. Defect clustering suggests that a small number of modules contain the majority of defects. By focusing the test effort on these modules or areas, testers can find more defects more efficiently and effectively, thus increasing the likelihood of meeting the stated test objective.

To achieve 100% statement coverage (SC) and 100% branch coverage (BC), only one test case is needed. This is because there is only one decision point in the program, which is the "IF OUTLOOK OPEN" condition. The program will always execute the "SWITCH PC ON" statement and the "START 'OUTLOOK'" statement. The "SEND MAIL" and "CLOSE OUTLOOK" statements will only be executed if the "IF OUTLOOK OPEN" condition is true, which covers both branches of the decision point. Therefore, one test case is sufficient to achieve 100% SC and 100% BC.

Equivalence partitioning is a software testing technique that reduces the number of test cases by dividing inputs into equivalence classes. It assumes that if a system processes one input from a class correctly, it will process others from the same class correctly. The technique involves identifying all inputs and outputs, grouping inputs into equivalence classes, and ensuring that test cases cover each class at least once. This helps to effectively test the system with fewer test cases.

Confirmation testing is performed to ensure that a defect or issue that was previously identified and fixed has been resolved correctly. This type of testing is done to validate that the fix implemented has effectively resolved the problem without introducing any new issues or unintended changes. It helps in verifying that the system is functioning as expected after the defect has been addressed, providing confidence that the fix was successful.