Buglyst Blog

Learn to debug under pressure.

Playbooks for fast pattern recognition, guides for the full investigation, and articles for the engineering judgment around the edges.

17 playbooks · 509 guides · 95 articles · 12 linked practice labs ·skip to practice

( 01 )Debugging playbooks

Fast pattern recognition for the production failures engineers see most often.

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( 02 )Deep debugging guides

Structured investigations for the failure modes engineers meet in real systems.

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( 03 )Engineering articles

Long-form thinking on debugging habits, observability, and the systems around the bug.

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Article

How to Reproduce a Flaky Test: From CI Logs to Reliable Failure

A practical guide to turning intermittent test failures into reliably reproducible bugs, with techniques ranging from loop testing to thread sanitizers.

Testing
Article

Property-Based Testing: Finding the Off-by-One That Lived in Production for 18 Months

A concrete story of how switching from example-based tests to property-based tests caught a timing bug that had survived code review, QA, and 18 months of production traffic.

Testing
Article

How We Reduced End-to-End Test Flakiness by 80% with Deterministic Seeding

After months of chasing intermittent failures in our CI pipeline, we implemented a three-part strategy — deterministic seeding, isolated state per test, and a structured retry budget — that cut flaky end-to-end test failures by 80%.

Testing
Article

Snapshot Testing: The 5 Hidden Failure Modes That Will Break Your CI

Snapshot tests seem like a safety net, but they often hide real bugs, bloat diffs, and silently break your CI. Here are the five failure modes I've seen in production and how to fix them.

Testing
Article

Testing Async Code: Avoiding Flakiness and False Positives in JavaScript

Async testing is full of traps: unhandled rejections, race conditions, and tests that pass when they shouldn't. Here's how to write reliable async tests in JavaScript.

Testing
Article

Testing Error Handling Code Paths: A Practical Approach

Error handling code is often the least tested and most brittle. Here's how to cover those paths with fault injection, mocks, and chaos engineering.

Testing