Systems | Development | Analytics | API | Testing

The rise of AI-assisted coding has transformed how software is built. With tools generating entire features in seconds, the bottleneck is no longer writing code—it’s verifying it. Because AI can generate boilerplate and handle API integrations instantly, more service changes are being pushed into authentication logic, API calls, and configurations. Teams desperately need a way to verify these changes before merging, especially when the code touches external dependencies.

White box testing is what separates teams that know their code works from teams that hope it does. High code coverage numbers can be misleading. A suite with 90% statement coverage can still miss the branch that throws a NullPointerException in production, or the loop condition that behaves differently on an empty list. White box testing is not just about running code – it’s about systematically verifying that every path, condition, and branch in your logic behaves the way you intended.

How we utilized all of our customer data to identify churn trends and prevent future loss.

Perforce Delphix vs. K2View — which one is better for your data management and compliance needs? Each provider has strengths and weaknesses, so it’s important that you find the right one that checks your boxes, prioritizes your top needs, and fits your use cases. In this blog, we’ll detail compare Delphix vs. K2view, including their key differences, use cases, integrations, and Delphix customer testimonies.

Agentic Testing and QA is a practice in which AI agents operate directly on a project — reading files, planning tasks, generating framework code, and interacting with a browser — rather than simply answering prompts inside a chat window. Tools like Claude Code bring this capability to the terminal, giving QA teams a command-line assistant that understands repository context, proposes changes before applying them, and generates test assets across Playwright, Selenium, and API testing workflows.

AI agents do not just respond. They interpret goals, use tools, follow workflows, apply context, and sometimes change real systems. That means they need a different kind of testing.

Security vulnerabilities in production environments rarely arrive one at a time. Recently, one of our enterprise Node.js support customers identified a collection of security advisories affecting their Node.js infrastructure. The affected environments were running Node.js v20 and v22 and included vulnerabilities not only within runtime-adjacent tooling but also in components distributed alongside Node.js deployments.