What is 'defense-in-depth' in the context of debugging?

Defense-in-depth involves adding validation checks at every layer of a call chain so that future errors are caught immediately at the source rather than failing deep in the system.

What is the main benefit of root cause tracing?

It ensures that you fix the actual source of a bug rather than just suppressing a symptom, preventing the issue from resurfacing elsewhere in your application.

How does this skill help with test pollution?

It provides strategies and scripts to isolate tests, running them one-by-one to identify the exact point where the environment or state becomes corrupted.

When should I use this skill instead of standard debugging?

Use this skill when an error occurs deep in execution with a long call chain, or when it is unclear exactly where invalid data was first introduced into the system.

Root Cause Tracing

Name: Root Cause Tracing
Author: seanGSISG

byseanGSISG

セキュリティとテスト

Systematically traces bugs backward through the call stack to identify and resolve original triggers rather than just treating symptoms.

概要

This skill provides a structured methodology for identifying the source of complex bugs that manifest deep within a software call stack. By prioritizing backward tracing over superficial fixes, it guides users through observing symptoms, instrumenting code with manual stack traces, and implementing multi-layered defense-in-depth validation to prevent regression. It is particularly effective for debugging test pollution, incorrect environment configurations, and data corruption issues where the manifestation point is far removed from the actual error source.

主な機能

Defense-in-depth implementation patterns for robust fixes
Systematic backward call stack tracing methodology
Test pollution identification using bisection scripts
0 GitHub stars
Automated instrumentation techniques for capturing stack traces
Strategic logging techniques for debugging deep execution errors

ユースケース

Debugging filesystem errors triggered by deep, nested library calls
Tracing the origin of invalid data passed through multiple abstraction layers
Identifying which specific test is causing state pollution in a large suite

概要

主な機能

Defense-in-depth implementation patterns for robust fixes
Systematic backward call stack tracing methodology
Test pollution identification using bisection scripts
0 GitHub stars
Automated instrumentation techniques for capturing stack traces
Strategic logging techniques for debugging deep execution errors

ユースケース

Debugging filesystem errors triggered by deep, nested library calls
Tracing the origin of invalid data passed through multiple abstraction layers
Identifying which specific test is causing state pollution in a large suite