Sarah Chen
QA Lead & Technical Writer, TestKase
Sarah is a QA lead and technical writer at TestKase with deep expertise in AI-powered testing, test strategy, and quality best practices. She writes about the intersection of AI and software quality.
- 8+ years in QA & Test Strategy
- AI & Machine Learning in Testing
Articles by Sarah Chen
Why Single-Page Accessibility Scans Miss Real Bugs (and What Multi-Page Audits Catch)
Single-URL accessibility scanners miss six entire categories of WCAG violations. Here's what falls through the gap, and how flow-aware audits catch the issues your users actually hit.
·14 min readColor Contrast: The #1 Accessibility Violation (and How to Fix It in 30 Minutes)
Color contrast is roughly 38% of every accessibility scan report. Here's the math, the 8 patterns that fail in 90% of apps, and a designer-developer playbook for fixing them without breaking your brand.
·13 min readWCAG 2.2 AA Compliance Checklist for Web Apps in 2026
A practical, engineer-grade WCAG 2.2 Level AA checklist with the exact tests, automated coverage, and a 4-week rollout plan for shipping accessible web apps.
·18 min readWe Gave Our Test Management Tool an AI Brain. Here's What Happened.
How we built an AI agent that manages test cases, cycles, and reports through conversation — and what we learned about what works and what doesn't.
·11 min readTestKase MCP Server: The First AI-Native Test Management Platform
TestKase ships the first MCP server for test management — connect Claude, Cursor, GitHub Copilot, and any AI agent to manage test cases, cycles, and reports.
·15 min readManual vs Automated Testing: When to Use Each
Compare manual and automated testing approaches. Learn when to use each, their pros and cons, and how to build a balanced QA strategy for your team.
·12 min readAI-Powered Test Case Generation: The Future of QA
Discover how AI-powered test case generation cuts QA writing time by 60%, boosts coverage to 90%, and transforms your testing workflow with smart prompts.
·26 min readThe QA Engineer's Guide to Working with AI Copilots
Practical guide for QA engineers using AI copilots for test case generation, code review, bug analysis, and automation — with prompts, metrics, and workflows.
·24 min readDefinition of Done for QA: What It Should Really Include
Learn what a strong Definition of Done should include for QA — testing criteria, automation gates, bug thresholds, and documentation checklists that ship quality.
·21 min readAI Test Maintenance: How Smart Tools Keep Test Suites Fresh
Learn how AI-powered tools maintain test suites by detecting stale tests, auto-healing selectors, syncing requirements, and cutting maintenance costs by 40-60%.
·22 min readExploratory Testing in Agile: Techniques That Find Real Bugs
Learn proven exploratory testing techniques for agile teams including session-based testing, charters, heuristics, and note-taking strategies that find critical bugs.
·23 min readPrompt Engineering for QA: Getting Better Results from AI Test Tools
Learn prompt engineering techniques for AI testing tools with practical templates, real examples, and methods to generate higher-quality test cases every time.
·20 min readPredictive Quality Analytics: Using AI to Forecast Defects
Discover how machine learning models predict software defects before they reach production. Learn data inputs, ML approaches, and practical implementation steps.
·19 min readUsing AI to Write Better Bug Reports (With Examples)
Use AI to write clearer, more actionable bug reports that developers can act on immediately. Includes before-and-after examples, prompts, and workflow tips.
·20 min readBehavior-Driven Development (BDD): Does It Actually Work?
An honest guide to BDD — when it delivers value vs. becomes overhead. Covers Gherkin, Cucumber, Three Amigos, anti-patterns, and real-world implementation.
·19 min readShift-Left Testing: How to Catch Bugs Before They're Expensive
Implement shift-left testing to catch bugs 10x cheaper. Learn requirements review, static analysis, TDD, and CI quality gates with real-world examples.
·20 min readAI Duplicate Detection in Test Suites: Why It Matters
Learn how AI-powered semantic duplicate detection finds redundant test cases, reduces suite maintenance by 20-30%, and reveals hidden coverage gaps.
·23 min readHow AI Is Changing Software Testing in 2026
Discover how AI transforms software testing with test generation, self-healing automation, defect prediction, and smarter QA workflows in 2026.
·23 min readHow to Write Test Cases That Actually Catch Bugs
Master boundary value analysis, equivalence partitioning, and negative testing techniques to write QA test cases that catch real bugs before production.
·20 min read