Key Takeaways Effective test automation in CI/CD requires strategic planning and the right integration approach to maximize both speed and quality. Start with a clear automation strategy that aligns with your development velocity and quality goals. The modern software landscape demands rapid delivery without compromising quality. The automation testing market is projected to reach $63.05… Continue reading Best Practices for Implementing Test Automation in CI/CD
Category: AI Testing
Your essential resource for AI testing. This category covers quality assurance strategies, evaluation frameworks, and best practices for testing Large Language Models (LLMs) and other generative AI systems. Learn how to ensure your AI applications are safe, reliable, and ready for production.
Real QA Challenges with AI-Generated Code and How to Tackle Them
The buzz around AI-generated code is undeniable. From intelligent autocompletion to entire function generation, AI is rapidly changing how we write software. Developers are experiencing unprecedented speed, freeing up time for more complex problem-solving. But if you’re a QA professional or a developer with a quality hat, a familiar question quickly arises: “How do we actually ensure… Continue reading Real QA Challenges with AI-Generated Code and How to Tackle Them
The AI Code Revolution: Ensuring Quality with Smarter Verification
The promise of AI-generated code is undeniably exciting. Developers are already leveraging tools to rapidly prototype, automate boilerplate, and even solve complex logical problems with unprecedented speed. But for every line of code an AI writes, a critical question emerges: How do we know it works? How do we ensure its quality, reliability, and adherence to requirements?… Continue reading The AI Code Revolution: Ensuring Quality with Smarter Verification
Shift Left on AI Generated Code: Why Pull Request Verification is Your New Quality Gate
The hum of AI in the developer’s toolkit is growing louder. From GitHub Copilot and Claude to ChatGPT and specialized AI code generator agents like Cursor, these intelligent assistants are no longer niche tools—they’re becoming indispensable for writing unit tests, generating regression tests, and even architecting complex systems at unprecedented speed. The promise? Exploding productivity,… Continue reading Shift Left on AI Generated Code: Why Pull Request Verification is Your New Quality Gate
Validate AI Code: Human-in-the-Loop Testing for AI Code Generator Agents
The landscape of software development is undergoing a seismic shift, driven by the unprecedented rise of AI coding assistants. Tools like GitHub Copilot, Cursor, Claude, ChatGPT and any other AI Generated Code agents have moved from novelty to everyday utility, promising unparalleled productivity boosts, faster iteration cycles, and a future where boilerplate code is a… Continue reading Validate AI Code: Human-in-the-Loop Testing for AI Code Generator Agents
Beyond the Basics: Advanced LLM Evaluation Metrics and Strategies for QA Success
The integration of Large Language Models (LLMs) into applications is rapidly transforming the software landscape. As we discussed in our Guide to LLM Testing and Evaluation previous post, while LLMs offer unprecedented capabilities, their non-deterministic nature presents unique and evolving challenges for quality assurance. As QA professionals and developers, we’ve moved past the initial awe… Continue reading Beyond the Basics: Advanced LLM Evaluation Metrics and Strategies for QA Success
A Guide to LLM Testing and Evaluation for Modern QA Teams
Introduction The world of software is undergoing a seismic shift. Large Language Models (LLMs) are no longer a novelty; they are being integrated into a vast array of applications, from customer support chatbots to sophisticated code generation tools. For QA professionals and developers, this represents a new frontier in software testing as well, one that… Continue reading A Guide to LLM Testing and Evaluation for Modern QA Teams