Which black-box test design technique is based on boundary values?

Which black-box test design technique is based on boundary values?

• A. Equivalence partitioning
• B. Boundary value analysis
• C. Decision table testing
• D. State transition testing

Answer: (B)

The technique that focuses specifically on boundary values is known as boundary value analysis. This black-box test design technique is centered around the idea that errors often occur at the edges of input ranges, making it critical to test these boundary conditions. Boundary value analysis involves selecting test cases that are at, just below, and just above the boundaries of input values. For example, if a system accepts input values between 1 and 100, relevant boundary values to test would include 1, 100, 0 (just below), and 101 (just above). This helps in identifying potential defects that may not be evident with tests that target only the typical or 'normal' input values. While equivalence partitioning also helps in identifying test cases based on input ranges, it does not focus specifically on the boundaries. Decision table testing and state transition testing serve different purposes; decision table testing is designed to address combinations of conditions and their expected outcomes, while state transition testing evaluates how a system responds to different states. Hence, boundary value analysis is the correct choice when specifically addressing testing around the limits of input values.

The technique that focuses specifically on boundary values is known as boundary value analysis. This black-box test design technique is centered around the idea that errors often occur at the edges of input ranges, making it critical to test these boundary conditions.

Boundary value analysis involves selecting test cases that are at, just below, and just above the boundaries of input values. For example, if a system accepts input values between 1 and 100, relevant boundary values to test would include 1, 100, 0 (just below), and 101 (just above). This helps in identifying potential defects that may not be evident with tests that target only the typical or 'normal' input values.

While equivalence partitioning also helps in identifying test cases based on input ranges, it does not focus specifically on the boundaries. Decision table testing and state transition testing serve different purposes; decision table testing is designed to address combinations of conditions and their expected outcomes, while state transition testing evaluates how a system responds to different states. Hence, boundary value analysis is the correct choice when specifically addressing testing around the limits of input values.