In "White-Box Testing", test cases are designed considering the internal "Structure" of the application. It focuses on the internal logic, algorithm, and code complexity, ensuring that each part of the code has been tested.

User Acceptance Testing (UAT) is the phase where the client/end-users test the software to ensure it aligns with their needs and requirements. It's the final testing phase before software deployment. The purpose of UAT is to validate the software's end-to-end business flow and its fit for the client's environment.

Backend Testing, as the name suggests, focuses on the interactions with databases, messaging queues, and other backend components. This ensures that data is processed and stored correctly, and messages are sent or received as expected, guaranteeing the robustness and reliability of backend operations.

Alpha testing is conducted in-house by developers and testers during the final stages of software development. It's a type of acceptance testing and is done before the software product is made available to the general public.

Black Box Testing is an approach where the tester doesn't have any knowledge about the internal workings of the system. It focuses on testing the application's functionality without concerning the internal code structures, making it the best choice for this scenario.

"Defect density" is a metric that measures the number of defects identified in a component or system divided by the size of the component or system (typically measured in KLOC or function points). It provides a normalized view of the quality and helps in comparing different releases.

Acceptance Testing is the phase of software testing where the system is tested for acceptability. Its main purpose is to evaluate the system's compliance with the business requirements and assess whether it is acceptable for delivery to the end users.

Load testing and stress testing are both forms of performance testing, but they serve different purposes. Load testing primarily focuses on how the system behaves under expected or heavy loads, determining its scalability. In contrast, stress testing intentionally pushes the system beyond its designed capacity to identify its breaking points and to see how it recovers from failures.

Data flow analysis, in the context of static analysis, primarily focuses on understanding and tracking the flow of data values through the paths of a program. It can help in identifying issues like the use of uninitialized variables, potential data leaks, and data dependencies.

Decision Table Testing is a systematic and comprehensive technique that captures different combinations of input values and preconditions in a table format. This approach ensures that testers evaluate all possible scenarios, especially when multiple conditions influence the outcome of a decision.