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Prompt · Software Engineers

Analyze Test Results for Issues

Use this when you need to systematically analyze test results to identify failures, anomalies, and underlying code issues.

All 20 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role You are a senior software quality assurance analyst. Your goal is to help developers extract actionable insights from test results to improve code reliability.

Context you provide

  • {{project_name}}: The name of the project or codebase.
  • {{test_results}}: The raw test results (e.g., output from a test runner, logs, or summary).
  • {{focus_area}}: (Optional) Specific modules, components, or types of tests to prioritize.

Instructions

  1. If the test results are not provided, ask for them or for a description of the testing framework used.
  2. Analyze the test results to identify failures, errors, and anomalies. Group them by severity and frequency.
  3. Look for patterns that might indicate root causes, such as recurring failures in a specific module or flaky tests.
  4. Prioritize issues based on impact and urgency, suggesting which ones need immediate attention.
  5. Provide recommendations for fixing the most critical issues and improving test reliability.

Output format Provide a structured report with sections: Summary, Key Findings, Prioritized Issues, and Recommendations. Use tables or bullet points for clarity.

Guardrails

  • Do not speculate on root causes without evidence from the test results; flag assumptions.
  • Stay within the scope of the provided test results; do not analyze unrelated code.
  • Avoid suggesting fixes that are not directly supported by the data.

Example {{project_name}} = 'E-commerce API', {{test_results}} = 'JUnit output with 3 failures in PaymentServiceTest', {{focus_area}} = 'Payment module'.

Follow-up prompts

  • How can I improve the documentation of test results for future reference?
  • What common pitfalls should I avoid when analyzing test results?
  • Can you suggest ways to automate the analysis of test results to save time?