FAQ

The next wave of test automation isn’t just about executing predefined scripts — it’s about predicting what to test, when to test, and where failures are most likely to occur. Predictive analytics, powered by machine learning and data insights, is emerging as a powerful ally in making automation smarter and more strategic.

When working with Jest testing, everything feels smooth until you hit those unpredictable test failures. You fix one issue, and suddenly two more appear — sound familiar? Debugging Jest can be tricky, especially when dealing with asynchronous code, flaky tests, or unexpected mock behaviors. But with the right techniques, it doesn’t have to be a painful process.

In today’s digital world, strong passwords are more important than ever. If you’re a developer looking to automate password creation, understanding how to leverage a JS random number generator is key. JavaScript offers several ways to produce randomness, with Math.random() being the most commonly used, but combining it smartly with characters and symbols makes password generation both simple and effective.

As large language models (LLMs) become integral to modern applications, ensuring their reliability is increasingly important. That’s where LLM unit testing comes in. Unlike traditional unit tests, testing LLMs involves not only checking for functional correctness but also evaluating performance, consistency, and edge-case behavior. Measuring coverage in these tests is key to understanding how well your model is being validated.

Working with legacy applications is one of those tasks that almost every developer or QA team will face at some point. These systems often lack proper documentation, have fragile dependencies, and usually come with years of “quick fixes” piled on top of one another. Yet, businesses rely heavily on them, which makes testing critical. That’s where functional test cases become the anchor for stability.