
Property-Based Testing in TypeScript with Fast-Check
How property-based testing finds the edge cases your unit tests miss: a practical guide to fast-check for generating inputs and verifying invariants.
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Software craft & practices · 55 articles · Page 4 of 5

How property-based testing finds the edge cases your unit tests miss: a practical guide to fast-check for generating inputs and verifying invariants.

A practical guide to load testing APIs: tool selection, realistic traffic patterns, performance baselines, bottleneck identification and common mistakes.

How to write technical documentation that engineers actually read — covering ADRs, runbooks, API docs, and documentation-as-code workflows.

Techniques for diagnosing memory leaks, excessive allocation, and OOM kills in production — covering heap snapshots, profiling tools, and common leak patterns.

How trunk-based development with short-lived branches reduces merge conflicts, speeds up delivery, and keeps the main branch always deployable.

Patterns for integration tests that are reliable, fast, and catch real bugs — covering database setup, API testing, and avoiding flaky test syndrome.

Practical functional programming patterns for TypeScript that improve code clarity without requiring a complete paradigm shift.

A practical guide to TypeScript generics that takes you from basic type parameters to advanced conditional types and utility patterns.

How to give code reviews that catch real bugs, share knowledge, and improve team velocity instead of creating bottlenecks.

When a request touches five services, each log is useless alone — distributed tracing ties them together with trace IDs, spans and context propagation.

Chaos engineering is the practice of deliberately injecting failures into production systems to discover weaknesses before they cause real outages.

Closures, event listeners, and uncleared timers — the most common memory leak patterns in Node.js and how to find them before they crash production.