bereniketech/systematic-debugging

Systematic Debugging

---

1. Overview

Random fixes waste time and create new bugs. Quick patches mask underlying issues.

Rule: ALWAYS find root cause before attempting fixes. Symptom fixes are failure. No fixes without root cause investigation first. If you haven't completed Phase 1, you cannot propose fixes.

---

2. When to Use

Use for ANY technical issue: test failures, bugs in production, unexpected behavior, performance problems, build failures, integration issues.

Use this ESPECIALLY when:

• Under time pressure (emergencies make guessing tempting)
• "Just one quick fix" seems obvious
• You've already tried multiple fixes
• Previous fix didn't work
• You don't fully understand the issue

Don't skip when:

• Issue seems simple (simple bugs have root causes too)
• You're in a hurry (rushing guarantees rework)

---

3. Phase 1 — Root Cause Investigation

BEFORE attempting ANY fix:

1. Read Error Messages Carefully

   • Don't skip past errors or warnings — they often contain the exact solution
   • Read stack traces completely
   • Note line numbers, file paths, error codes

2. Reproduce Consistently

   • Can you trigger it reliably? What are the exact steps?
   • Does it happen every time?
   • If not reproducible, gather more data — don't guess

3. Check Recent Changes

   • What changed that could cause this? Git diff, recent commits
   • New dependencies, config changes, environmental differences

4. Gather Evidence in Multi-Component Systems

   When a system has multiple components (CI → build → signing, API → service → database):

   Before proposing fixes, add diagnostic instrumentation:

   For EACH component boundary:
     - Log what data enters component
     - Log what data exits component
     - Verify environment/config propagation
     - Check state at each layer
   
   Run once to gather evidence showing WHERE it breaks
   THEN analyze evidence to identify failing component
   THEN investigate that specific component
   

5. Trace Data Flow

   When the error is deep in a call stack, see root-cause-tracing.md in this directory for the complete backward tracing technique.

   Quick version: Where does the bad value originate? What called this with the bad value? Keep tracing up until you find the source. Fix at source, not at symptom.

---

4. Phase 2 — Pattern Analysis

Find the pattern before fixing:

1. Find Working Examples — Locate similar working code in same codebase
2. Compare Against References — If implementing a pattern, read reference implementation COMPLETELY. Don't skim.
3. Identify Differences — List every difference between working and broken, however small
4. Understand Dependencies — What other components, settings, config, environment does this need?

---

5. Phase 3 — Hypothesis and Testing

Scientific method:

1. Form Single Hypothesis — State clearly: "I think X is the root cause because Y." Be specific.
2. Test Minimally — Make the SMALLEST possible change to test hypothesis. One variable at a time. Don't fix multiple things at once.
3. Verify Before Continuing — Did it work? Yes → Phase 4. Didn't work? Form NEW hypothesis. Don't add more fixes on top.
4. When You Don't Know — Say "I don't understand X." Don't pretend to know. Research more.

---

6. Phase 4 — Implementation

Fix the root cause, not the symptom:

1. Create Failing Test Case — Simplest possible reproduction. Automated test if possible. Must have before fixing.
2. Implement Single Fix — Address the root cause identified. ONE change at a time. No "while I'm here" improvements. No bundled refactoring.
3. Verify Fix — Test passes now? No other tests broken? Issue actually resolved?
4. If Fix Doesn't Work — STOP. Count: How many fixes have you tried?
   • If < 3: Return to Phase 1, re-analyze with new information
   • If >= 3: STOP and question the architecture (see below)

Rule: If 3+ fixes have failed, STOP and question fundamentals. Pattern signs: each fix reveals new shared state/coupling, fixes require massive refactoring, each fix creates new symptoms elsewhere. This is NOT a failed hypothesis — this is a wrong architecture. Discuss with the user before attempting more fixes.

---

7. Red Flags — STOP and Follow Process

If you catch yourself thinking:

• "Quick fix for now, investigate later"
• "Just try changing X and see if it works"
• "Add multiple changes, run tests"
• "Skip the test, I'll manually verify"
• "It's probably X, let me fix that"
• "I don't fully understand but this might work"
• "One more fix attempt" (when already tried 2+)
• Each fix reveals new problem in different place
• Proposing solutions before tracing data flow

ALL of these mean: STOP. Return to Phase 1.

---

8. Common Rationalizations

| Excuse | Reality | |--------|---------| | "Issue is simple, don't need process" | Simple issues have root causes too. Process is fast for simple bugs. | | "Emergency, no time for process" | Systematic debugging is FASTER than guess-and-check thrashing. | | "Just try this first, then investigate" | First fix sets the pattern. Do it right from the start. | | "I'll write test after confirming fix works" | Untested fixes don't stick. Test first proves it. | | "Multiple fixes at once saves time" | Can't isolate what worked. Causes new bugs. | | "Reference too long, I'll adapt the pattern" | Partial understanding guarantees bugs. Read it completely. | | "One more fix attempt" (after 2+ failures) | 3+ failures = architectural problem. Question pattern, don't fix again. |

---

9. Supporting Techniques

These techniques are available in this directory:

• root-cause-tracing.md — Trace bugs backward through call stack to find original trigger
• defense-in-depth.md — Add validation at multiple layers after finding root cause
• condition-based-waiting.md — Replace arbitrary timeouts with condition polling
• find-polluter.sh — Find test pollution in test suites

---

10. Quick Reference

| Phase | Key Activities | Success Criteria | |-------|---------------|------------------| | 1. Root Cause | Read errors, reproduce, check changes, gather evidence | Understand WHAT and WHY | | 2. Pattern | Find working examples, compare | Identify differences | | 3. Hypothesis | Form theory, test minimally | Confirmed or new hypothesis | | 4. Implementation | Create test, fix, verify | Bug resolved, tests pass |