Boundary Value Analysis (BVA)

Boundary Value Analysis (BVA) is a software testing technique usedto identify errors around the boundaries of input ranges.

Here’s a simple overview along with its advantages and disadvantages:

Concept:

BVA focuses on testing the boundaries of input values, as errorsoften occur at the edges or limits of acceptable input ranges

Test Cases:

Test cases are designed to test values at the lower and upperboundaries of valid input ranges, as well as just inside and just outside those boundaries.

Example:

If a software program accepts input values from 1 to 100, boundary value analysis would test values like 0, 1, 2, 99, 100, and 101 to ensure the softwarebehaves correctly.

Advantages:

BVA efficiently identifies errors that are likely to occur at the boundaries of inputranges, improving the quality of the software.
By focusing testing efforts on boundary values, BVA helps reduce the number oftest cases needed while still providing comprehensive coverage.
BVA provides clear guidelines for selecting test cases, making it easy tounderstand and apply, even for testers with limited experience.

BVA primarily focuses on boundary values, which may not detect errors that occurwithin the input range.
In complex systems with multiple input parameters and dependencies, identifyingall relevant boundary values can be challenging.
BVA may overlook scenarios where errors occur due to interactions betweendifferent input values, as it primarily targets individual boundaries.

Structure:

Decision tables typically consist of columns representing different conditions or factors, and rows representing combinations of conditions andcorresponding actions or outcomes.

Example:

In a decision table for a loan approval system, conditions such as credit score, income level, and loan amount might be represented in columns, withrows representing different combinations of these conditions and actions such as”approve” or “reject.”

Decision tables provide a clear and structured representation of complex decisionlogic, making it easier for stakeholders to understand and verify business rules.
Decision tables ensure that all possible combinations of conditions and corresponding actions are considered, reducing the likelihood of over looking critical scenarios.
Decision tables are easy to update and maintain, allowing for quick adjustments tobusiness rules or logic as requirements change.

Decision tables can become complex and difficult to manage, especially for systems with numerous conditions and actions.
As the number of conditions and actions increases, decision tables may becomeunwieldy and difficult to interpret, leading to potential errors or oversights.
Designing a decision table requires careful analysis and planning to ensure that all relevant conditions and actions are accurately represented, which can be time consuming.