systematic-debugging

# Systematic Debugging ## Overview Random fixes waste time and create new bugs. Quick patches mask underlying issues. **Core principle:** ALWAYS find root cause before attempting fixes. Symptom fixes are failure. **Violating the letter of this process is violating the spirit of debugging.** ## The Iron Law ``` NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST ``` If you haven't completed Phase 1, you cannot propose fixes. ## 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 ## The Four Phases You MUST complete each phase before proceeding to the next. ### 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 system has multiple components:** **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 error is deep in call stack:** - Where does bad value originate? - What called this with bad value? - Keep tracing up until you find the source - Fix at source, not at symptom ### Phase 2: Pattern Analysis **Find the pattern before fixing:** 1. **Find Working Examples** - Locate similar working code in same codebase - What works that's similar to what's broken? 2. **Compare Against References** - If implementing pattern, read reference implementation COMPLETELY - Don't skim - read every line - Understand the pattern fully before applying 3. **Identify Differences** - What's different between working and broken? - List every difference, however small - Don't assume "that can't matter" 4. **Understand Dependencies** - What other components does this need? - What settings, config, environment? - What assumptions does it make? ### Phase 3: Hypothesis and Testing **Scientific method:** 1. **Form Single Hypothesis** - State clearly: "I think X is the root cause because Y" - Write it down - Be specific, not vague 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 - Ask for help - Research more ### 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 - Use the `test-driven-development` skill for writing proper failing tests 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** - DON'T attempt Fix #4 without architectural discussion 5. **If 3+ Fixes Failed: Question Architecture** **Pattern indicating architectural problem:** - Each fix reveals new shared state/coupling/problem in different place - Fixes require "massive refactoring" to implement - Each fix creates new symptoms elsewhere **STOP and question fundamentals:** - Is this pattern fundamentally sound? - Are we "sticking with it through sheer inertia"? - Should we refactor architecture vs. continue fixing symptoms? **Discuss with your human partner before attempting more fixes** ## 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+) **ALL of these mean: STOP. Return to Phase 1.** ## 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 |