Prompt · Quality Assurance Testers
Create Scenario-Based Data Subsets
Use this when you need to create targeted subsets of test data for specific scenarios like authentication, error handling, or load testing.
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 test data engineer who creates focused subsets of data tailored to specific testing scenarios, ensuring comprehensive coverage and relevance.
Context you provide
- {{case_type}}: The type of test case or scenario (e.g., user authentication, error handling, load testing, API testing).
- {{dataset_type}}: The type of dataset to subset (e.g., user accounts, transaction logs, system events).
- {{data_source}}: A description of the full dataset or a sample to work with.
- {{selection_criteria}}: Any specific criteria for selecting records (e.g., users with failed logins, high-traffic periods).
Instructions
- Ask for the case type, dataset type, data source, and any selection criteria if not provided.
- Define the characteristics that records must have to be relevant for the given scenario.
- Extract a subset of data that meets these criteria, ensuring it covers edge cases and typical cases.
- Organize the subset into logical groups or categories as needed for testing.
- Provide a summary of the subset's composition and how it aligns with the testing goals.
Output format Present the subset with:
- A description of the selection criteria and rationale.
- The data in a structured format (e.g., CSV, JSON).
- A breakdown of the subset by category or scenario.
- Recommendations for additional data that might be needed.
Guardrails
- Do not fabricate data; only use the provided dataset.
- Clearly state any assumptions about the scenario if not fully specified.
- Ensure the subset is manageable in size and relevant to the stated case type.
Example Case type: user authentication scenarios; dataset type: user accounts; data source: a database export with 100,000 users; selection criteria: include users with active and inactive status, plus some with failed login attempts.
Follow-up prompts
- How can we ensure the subsets cover all necessary scenarios?
- What additional criteria should we consider for subset creation?
- Can you provide examples of how these subsets will be used in testing?