AI-powered testing platform. Write tests in plain English, run them everywhere.
Testing
AI coding assistants have fundamentally changed how developers write software. They've also created a new question nobody had to answer before: when your AI writes the code, who makes sure the code actually works? This comparison covers the four most popular AI coding tools — Cursor, GitHub Copilot, Claude
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
Testing
The Agile Testing Quadrant is a useful model. But like most testing frameworks, it's described in abstract terms that don't immediately translate to Monday morning decisions. This guide makes it concrete: how QA teams actually use the quadrant in sprint planning, what they do in each
Testing
Most teams have a testing gut feeling—they write unit tests, some integration tests, maybe some end-to-end tests. What they often lack is a framework for thinking about why each type of test exists and what purpose it serves. The Agile Testing Quadrant provides that framework. Developed by
Fuzz Testing
Basic AFL++ usage — compile with afl-clang-fast, create a seed corpus, run afl-fuzz — finds bugs. Advanced AFL++ usage finds them 10–100x faster, or finds bugs that basic usage misses entirely. This post covers the techniques that make AFL++ effective against hard targets: persistent mode, comparison logging, custom
Usability Testing
WCAG compliance and accessible usability are not the same thing. A product can pass automated accessibility checks and still be unusable by screen reader users, people with cognitive disabilities, or users with motor impairments. Accessibility usability testing closes that gap: testing with real assistive technology users to find the problems
Acceptance Testing
Ask ten developers what the difference is between acceptance testing and integration testing, and you'll get ten different answers. The confusion is understandable — both test how multiple components work together, both can run against real systems, and both often use similar tooling. But they serve fundamentally different purposes,
CI/CD
"It works on my machine" is a testing problem, not a bragging rights problem. When your local environment differs from CI, which differs from staging, which differs from production, your tests are lying to you. Docker-based test environments solve this by making environments explicit, reproducible, and version-
CI/CD
A test suite that takes 45 minutes to run is a test suite that gets skipped. Developers waiting for feedback lose flow, start stacking commits, and begin treating CI as a formality rather than a safety net. Parallel test execution is the most impactful lever you have for keeping test
API Testing
If you write Java and need to test REST APIs, REST Assured is the most popular library for the job. It lets you write readable, expressive HTTP tests that fit naturally into a JUnit or TestNG test suite. This tutorial walks you through everything from initial setup to writing your
Acceptance Testing
Choosing an acceptance testing tool is a decision that shapes how your team writes tests, who can contribute to them, and how sustainable your test suite will be over time. The right tool depends on your application type, team expertise, stakeholder involvement needs, and how much you value different trade-
Test Automation
AccelQ and Selenium solve the same problem — automating browser tests — but they make completely different assumptions about who's doing the work and what skills they have. Picking the wrong one for your team isn't just a tooling mistake; it's a months-long detour. The