AI Testing
Qodo (formerly CodiumAI) generates unit tests automatically using AI. Install Qodo Gen in VS Code or JetBrains, select a function, run /test, and get a complete test file with assertions for happy paths, edge cases, and error scenarios. This guide covers setup, the test generation workflow, and what to do
Testing
You've hit 100% code coverage. Every line, every branch, every condition — green. Time to ship with confidence, right? Not quite. Code coverage tells you which lines were executed during tests. It says nothing about whether your tests would catch a bug if one appeared. Mutation testing does. The
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
AI Testing
Agentic testing means AI agents that autonomously handle steps in the testing cycle — creating tests, running them, analyzing failures, and fixing issues — without waiting for explicit human instruction at each step. This guide covers the patterns, tools, and implementation approach for teams adopting agentic testing workflows in 2026. Key Takeaways
QA Metrics
Test automation has upfront costs (writing, infrastructure) and ongoing costs (maintenance) set against time savings (faster test execution, fewer manual regression cycles). The ROI equation is straightforward once you have the right inputs. This post gives you the formula, walks through a worked example, and shows how to calculate break-
QA Metrics
MTTD (Mean Time to Detect) measures how long bugs hide before being found. MTTR (Mean Time to Repair) measures how long fixes take. Both are lagging indicators of QA maturity — but both can be systematically reduced through specific practices. This post gives you the definitions, benchmarks, and reduction strategies. Key
QA Metrics
QA investment pays back 4–15× depending on when bugs are caught. Bugs found in production cost 30× more to fix than bugs found in requirements. This post gives you the formulas to calculate your actual ROI and the narrative to present it upward. Key Takeaways * The IBM Systems Sciences
QA Metrics
The DORA metrics measure software delivery performance across four dimensions. Elite teams deploy more often and break things less — because they invest in test automation. This post maps each DORA metric to specific testing practices and shows how to improve your scores. Key Takeaways * DORA's four metrics: Deployment
QA Metrics
Most engineering teams track too few QA metrics (just pass/fail) or too many (every metric their CI tool exposes). This post identifies the five metrics that actually predict QA health, explains what each one tells you, and gives you targets and measurement approaches for each. Key Takeaways * Test coverage
Cross-Browser Testing
CSS looks different in different browsers. Safari lags on newer features. Firefox interprets certain specifications differently from Chrome. Internet Explorer is thankfully gone, but Edge, Safari, and Firefox all have their own quirks. This guide covers the most common cross-browser CSS issues, the tools that catch them, and the
Cross-Browser Testing
Selenium Grid lets you run tests across multiple browsers and machines in parallel by routing test commands from a central hub to registered browser nodes. Grid 4, the current version, supports standalone mode, hub/node mode, and fully distributed mode. Docker Selenium makes spinning up a cross-browser grid trivial.
Cross-Browser Testing
Safari is the hardest browser to automate. Its WebDriver implementation is more restrictive than Chrome or Firefox, it can only run on macOS and iOS hardware, Apple Silicon introduced new compatibility issues, and the WebKit engine has quirks that no other browser shares. This guide covers the specific challenges of