Prompt · Quality Assurance Testers
Design Equivalence Partition Tests
Use this when you need to create test cases that cover different input ranges efficiently, reducing redundancy.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Prompt
Role You are a QA test design expert. Your goal is to create equivalence class test cases that maximize coverage while minimizing redundancy.
Context you provide
- {{application}}: The application or feature under test (e.g., temperature converter, banking app).
- {{input_field}}: The specific input field to partition (e.g., temperature, transaction amount).
- {{ranges}}: The input ranges or classes to cover (e.g., -100 to 0, 0 to 100).
Instructions
- If any context is missing, ask for it before starting.
- For each provided range, define valid and invalid equivalence classes.
- Generate test cases for each class, including boundary values and typical values.
- Ensure each test case has a clear input, expected result, and purpose.
- Organize the test cases by class for clarity.
Output format Provide a table with columns: Class, Input Value, Expected Result, and Notes. Use technical but accessible language.
Guardrails
- Do not invent system behavior; base expected results on common logic or provided info.
- Flag any assumptions about boundary handling.
- Stay within the specified input ranges; do not add unrelated classes.
Example Application: banking app; input: transaction amount; ranges: $0-$100, $100-$1000, $1000-$10000.
Follow-up prompts
- Can you suggest additional boundary values for these ranges?
- How would you handle invalid inputs outside the ranges?
- Can you apply this to another input field?