diagnose

To find the root cause of a hard-to-reproduce software bug, use a structured, hypothesis-driven workflow that separates facts from assumptions, generates multiple root-cause hypotheses, and gathers minimal runtime evidence to validate them.

Hypothesis-driven debugging is a structured approach that generates distinct root-cause hypotheses and tests them with minimal runtime instrumentation. Use it for incident management when symptoms are unclear, reproducibility is hard, or the root cause is unknown.

Systematically diagnose unexpected behavior by following a workflow of symptom understanding, hypothesis creation, and evidence-guided testing. This process isolates the root cause and outputs a formal diagnosis without performing fixes or rewriting code.

Yes, you can plan and apply minimal, safe runtime instrumentation to gather evidence that validates or falsifies specific root-cause hypotheses during an incident. This ensures you confirm the diagnosis with data before attempting remediation.

The best way to investigate unclear symptoms is to first clarify and document visible facts to separate them from assumptions. This symptom understanding phase prevents premature fixes and grounds the subsequent root-cause hypothesis generation in observed evidence.

Debugging fails to identify the root cause of mysterious behavior when it skips structured fact-finding and relies on assumptions. A formal diagnosis requires generating multiple hypotheses and collecting supporting runtime evidence to validate them before concluding.