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GitHub Code Quality Trends: Measuring Engineering Health Across Repositories
Learn how to use GitHub code quality trends to measure engineering health across repositories and build meaningful software quality metrics for development teams.
GitHub Code Quality Trends: Building Engineering Health Dashboards from Repository Data
Learn how to build engineering health dashboards using GitHub repository data and track code quality trends, development performance, and team health.
Building Agentic QA Pipelines with Browser Automation and .NET
Learn how to build agentic QA pipelines with Playwright for .NET and AI agents, including browser automation, agent memory, tool control, execution limits, and testing best practices.
Benchmarking AI-Generated Unit Tests Against Human-Written Tests
Learn how to benchmark AI-generated unit tests against human-written tests using code coverage, mutation scores, defect detection, false positives, readability, and maintainability.
Building AI Code Review Pipelines with GitHub Copilot Agent Plugins
Learn how to build automated AI code review pipelines with GitHub Copilot Agent Plugins, repository-specific tools, coding rules, and automated review workflows.
Building Trace-Based Release Gates for AI Applications
Build trace-based release gates for AI applications using evaluation metrics, execution traces, quality thresholds, regression detection, and automated CI/CD checks to prevent unreliable AI releases.
Testing AI Agents with Synthetic Enterprise Documents
Test AI agents with synthetic enterprise documents to evaluate extraction accuracy, grounding, hallucinations, edge cases, document variations, and system reliability under controlled conditions.
Building Release Gates for AI-Generated Code in Enterprise Repositories
Build release gates for AI-generated code in enterprise repositories using automated security, testing, dependency, quality, and architecture checks before production deployment.
Testing Flaky .NET Tests with Historical Failure Analysis
Detect flaky .NET tests using historical failure analysis to identify recurring failures, distinguish regressions from instability, and improve automated testing reliability.
Separating Flaky Tests from Regressions with Microsoft.Testing.Platform
Discover how Microsoft.Testing.Platform can help distinguish flaky tests from genuine regressions using test history, failure patterns, and CI pipeline diagnostics.
Testing Global .NET Test Timeouts with Microsoft.Testing.Platform
Learn how global test timeouts and maximum-failure controls in Microsoft.Testing.Platform can improve CI reliability and prevent stalled or excessive test runs.
Testing MCP Servers for Schema Drift and Tool Compatibility
Prevent AI agent failures by testing MCP server schema drift and tool compatibility. Ensure robust contracts for reliable AI interactions.
Testing MCP Tool Contracts with Contract-Based Integration Tests
Master MCP tool contracts with robust testing. Ensure API stability, prevent regressions, and build reliable AI integrations.
Testing Declarative AI Workflows with Failure Injection
Master declarative AI workflow testing with failure injection. Ensure robust error handling, recovery, and reliability in production.
Building MCP Load Tests for Stateless Agent Workloads
Master MCP load testing for stateless AI agent workloads. Optimize performance, identify bottlenecks, and ensure scalability with .NET.
Extended Development Teams for Flexible Software Delivery
Boost software delivery with extended development teams. Gain flexible capacity, specialized skills, and maintain project control.
Playwright Testing for ASP.NET Core Applications: A Practical Guide
Master Playwright for ASP.NET Core E2E testing. Learn setup, writing tests, best practices, and CI/CD integration for reliable web app validation.
Test Automation Best Practices with Microsoft Playwright
Master Microsoft Playwright with best practices for reliable, scalable, and maintainable test automation. Boost confidence and speed.
Performance Testing with Playwright: Measuring Web Performance Effectively
Learn how to perform basic performance testing with Playwright
Building AI-Powered Service Dependency Intelligence Platforms with .NET
Build AI-powered service dependency intelligence platforms with .NET to understand, manage, and reduce complexity in distributed systems.
AI-Powered Test Data Generation for Enterprise .NET Applications
Leverage AI for realistic, domain-specific test data generation in .NET apps. Enhance testing efficiency, coverage, and application quality.
Building AI-Powered Software Dependency Intelligence with .NET
Leverage .NET and AI for intelligent software dependency management, enhancing security, reliability, and developer productivity.
AI-Powered Regression Testing Pipelines for Enterprise .NET Applications
Boost enterprise .NET app quality with AI-powered regression testing. Automate test generation, prioritization, and failure analysis for faster, reliable releases.
Building AI-Powered Software Inventory Intelligence Platforms
Transform software inventories into intelligent platforms with AI. Gain visibility into dependencies, risks, and operational impact.
Building AI-Powered Software Delivery Insights Platforms
Unlock AI-powered software delivery insights. Transform data into actionable intelligence for better decisions and engineering excellence.
AI-Powered API Discovery and Cataloging in Enterprise Applications
Unlock API visibility and governance with AI-powered discovery and cataloging. Streamline development, reduce duplication, and boost productivity.
AI-Powered Test Case Generation for Enterprise .NET Applications
Automate .NET test case generation with AI. Enhance coverage, reduce errors, and accelerate enterprise application delivery.
AI Quality Assurance: Testing Strategies for LLM-Powered Applications
Master AI quality assurance for LLM apps. Explore testing strategies for accuracy, relevance, security, and reliability.
AI-Powered Release Management: Using Intelligence to Improve Software Delivery
Unlock faster, more reliable software delivery with AI-powered release management. Reduce risk, boost confidence, and optimize your CI/CD.
AI Testing Gap: Why Developers Adopt Coding Agents Faster Than Testing Agents
Explore the AI Testing Gap: why coding agents are adopted faster than testing agents and how to bridge the divide for better software delivery.
