Crafting AI Prompts for Generating Boundary Value Analysis (BVA) Test Cases

Boundary Value Analysis (BVA) is one of the most effective and widely used test case design techniques in software testing. It focuses on identifying defects at the boundaries of input ranges, where issues are most likely to occur. With advancements in AI, testers can now automate the process of generating BVA test cases using well-structured prompts.

In this article, we’ll explore how to create effective AI prompts for generating BVA test cases, the importance of BVA, and why leveraging AI in this process can enhance testing efficiency.

Boundary Value Analysis is a black-box testing technique used to test values at the edges of input domains. Testing at boundaries is essential because defects are more likely to occur at these points due to programming errors or overlooked edge conditions.

For example, if a field accepts numeric input between 1 and 100:

• Boundary values to test include: 1, 100 (valid values), and 0, 101 (invalid values).

BVA ensures that the system behaves correctly when inputs are at or near these boundaries.

Also Read: Test Case Design Techniques: A Guide to Effective Software Testing

Manually designing BVA test cases can be time-consuming, especially for complex systems with multiple input fields and conditions. AI tools simplify this process by automating the generation of BVA test cases based on system requirements.

Benefits of Using AI for BVA Test Cases:

1. Efficiency: AI can quickly generate hundreds of test cases for even the most complex input scenarios.
2. Accuracy: AI eliminates human error, ensuring that no critical boundary values are missed.
3. Scalability: AI can handle multiple fields, conditions, and constraints simultaneously.
4. Consistency: AI-generated test cases follow a structured format, making them easier to understand and execute.

Also Read: Mastering Test Case Writing and 90% Coverage with BetterCases

To harness the power of AI for BVA, it’s important to provide a clear and structured prompt. A good AI prompt should specify:

• The input field(s) and their valid ranges.
• The required boundary values (e.g., lower boundary, upper boundary).
• The desired output format for the test cases.

Example AI Prompt

Prompt:

"Generate Boundary Value Analysis (BVA) test cases for the given input field or system requirement. Include test cases for values at the lower boundary, upper boundary, just below the lower boundary, and just above the upper boundary. Each test case should contain the input value, expected output, and a brief description of the scenario."

Example Scenario for Context:

"The system accepts numeric input for a 'user age' field, with valid values ranging from 18 to 65 (inclusive)."

Output Format Example:

 1. Input Value: 18 (Lower Boundary)

Expected Output: Accepted

Description: Testing the system's behavior at the minimum valid age.

 2. Input Value: 17 (Just Below Lower Boundary)

Expected Output: Rejected

Description: Testing the system's behavior just below the minimum valid age.

 3. Input Value: 65 (Upper Boundary)

Expected Output: Accepted

Description: Testing the system's behavior at the maximum valid age.

 4. Input Value: 66 (Just Above Upper Boundary)

Expected Output: Rejected

Description: Testing the system's behavior just above the maximum valid age.

Also Read: Automated Test Case Creation: A Guide to Boosting Software Quality and Efficiency

Example AI Prompt for Multiple Fields

For systems with multiple input fields, the prompt should specify all relevant fields and their ranges.

Prompt:

"Generate Boundary Value Analysis (BVA) test cases for the following input fields:

1. 'User age' (valid range: 18 to 65).
2. 'Salary' (valid range: $30,000 to $120,000). Include test cases for boundary values and edge conditions for both fields. Output a structured list of test cases with input values, expected results, and descriptions."

Expected Output Example:

 1. Input Values: Age = 18, Salary = $30,000 (Lower Boundary)

Expected Output: Accepted

Description: Testing the lower boundary for both fields.

 2. Input Values: Age = 17, Salary = $29,999 (Just Below Lower Boundary)

Expected Output: Rejected

Description: Testing just below the valid range for both fields.

 3. Input Values: Age = 65, Salary = $120,000 (Upper Boundary)

Expected Output: Accepted

Description: Testing the upper boundary for both fields.

 4. Input Values: Age = 66, Salary = $120,001 (Just Above Upper Boundary)

Expected Output: Rejected

Description: Testing just above the valid range for both fields.

Also Read: Mastering Test Case Writing and 90% Coverage with BetterCases

AI prompts can be customized based on the complexity of the system under test. For example:

• For Text Fields: "Generate BVA test cases for a username field with a valid length of 5-15 characters."
• For Dropdown Options: "Generate BVA test cases for a dropdown with options ranging from 1 to 10."
• For Date Fields: "Generate BVA test cases for a date field accepting dates between 01/01/2000 and 12/31/2025."

The clearer and more specific the prompt, the better the results from the AI tool.

• Be Specific: Clearly define the input fields, valid ranges, and any constraints.
• Provide Context: Include a brief description of the system or field being tested.
• Request a Structured Format: Specify the output format, including input values, expected results, and descriptions.
• Test the Prompt: Run the prompt with a simple scenario first to ensure the AI understands your requirements.

Boundary Value Analysis is a critical test case design technique that ensures systems are thoroughly tested at their most vulnerable points—the boundaries. By leveraging AI tools and crafting effective prompts, testers can automate the generation of BVA test cases, saving time and improving accuracy.

Whether you’re testing numeric fields, text inputs, or complex systems with multiple conditions, a well-structured AI prompt is the key to unlocking the full potential of AI-powered testing tools. Start experimenting with tailored prompts today to streamline your testing process and achieve better software quality.