Testing strategy guides — how to plan, prioritize, and structure QA for your team or product.
Test Automation
Some outputs are too complex to specify with traditional assertions. A PDF report with hundreds of fields, a JSON API response with nested structures, a rendered HTML email, a generated CSV — writing assertions for every field is tedious and brittle. Change one field name and a hundred assertions break. Approval
Testing
Most test strategies are built around tooling: "we use Jest for unit tests, Cypress for E2E, and k6 for load testing." The problem with tool-centric strategies is that tools tell you what you're running, not what you're covering. You can have a fully
Acceptance Testing
Ask ten developers what the difference is between acceptance testing and integration testing, and you'll get ten different answers.
A/B Testing
The failure mode for most A/B tests isn't statistical — it's design. Teams write bad hypotheses, measure the wrong metrics, run tests too short, or contaminate the test population. By the time they realize the error, weeks of data are worthless. Good A/B test design
Testing Strategy
When a test fails in a distributed system, the error message tells you what failed — not where, why, or which of the twelve services involved was responsible. Distributed tracing in your test suite gives you the full execution path for every test run, turning hours of log-digging into a
Database Testing
Backend-as-a-Service (BaaS) platforms have become a default choice for teams who want authentication, databases, storage, and real-time subscriptions without building backend infrastructure from scratch. Platforms like Appwrite, Nhost, PocketBase, Xata, and Supabase each offer Firebase-style convenience with different trade-offs. Testing BaaS-backed applications requires
Shift-Left Testing
The software testing world has polarized around two strategies: shift-left (test early, in development) and shift-right (test in production, with real users).
No-Code Testing
Few debates in QA generate more heat than codeless versus scripted testing.
Test Automation
Quality observability means using data from production — real user behavior, errors, performance metrics — as direct input for your test suite. Instead of guessing which scenarios matter most, you test what users actually do. This guide covers how to implement quality observability using health checks, production monitoring, and feedback loops that
AI Testing
By 2026, more than half of code committed to GitHub is generated or substantially assisted by AI tools like Claude Code, Cursor, and GitHub Copilot. AI-generated code ships faster and introduces failure modes that traditional testing approaches miss. This guide covers how to build a testing strategy that scales
Testing Strategy
Exploratory testing gets dismissed in some organizations because it looks unstructured from the outside.
Deployment Testing
Feature flags (also called feature toggles or feature switches) are one of the most powerful tools in a modern engineering team's toolkit.