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In contemporary software engineering, it is not sufficient to simply confirm that software applications function perfectly across all features – they also need to behave correctly with real users in real worlds. In this context, scenario testing has a significant role to play. Scenario testing fills the gap between functional testing and real user experience based on validating software by simulating end-to-end user journeys.

Debugging React Native apps can be challenging, but using the right tools and techniques makes it manageable. Here’s what you need to know.

Cursor is fantastic at cranking out code changes. I recently used it to splice a brand-new downstream API call into one of our Go microservices, and the diff looked great. The unit tests finished before I lifted my coffee mug, yet I still had zero certainty the change would survive contact with real traffic. That gap is all about integration tests, so I paired Cursor with proxymock and the outerspace-go demo service to prove the behavior end to end.

AI testing careers are shifting in ways that most people in QA are not fully prepared for, and the changes are creating opportunities that did not exist even a few years ago.

In late 2024, Tricentis embarked on its own SAP transformation — migrating from NetSuite to a greenfield implementation of SAP S/4HANA Finance. This blog kicks off a series that will follow Tricentis’ migration journey, from planning and implementation through to outcomes and impact.

Each year, right on schedule, a new version of PHP is released at the end of November. So, how much faster is this new release across popular frameworks and applications? Our tests show that, in general, the performance between 8.2, 8.3, 8.4 and 8.5 does not move much for a Laravel, Symfony and WordPress demo application. Moving to the newest PHP version isn’t a magic shortcut to better performance. Not everything is bleak, though.

At Koyeb, we provide high-performance serverless infrastructure for intensive applications across CPUs, GPUs, and accelerators. We take code, build it, and run it in fully isolated, secure microVMs on bare-metal servers around the world. We scale automatically when needed, down to zero when idle, with cold starts as low as 250ms. Over the past few months, we’ve been working with an increasing number of teams using Koyeb to orchestrate and run AI-generated code at massive scale.

Learn about enhancements to the TimesFM foundation model that performs "zero-shot" forecasting, now available for BigQuery and AlloyDB.

Have you ever considered how well-tested your.NET code simply is? Many teams feel their test suite is complete until a bug makes its way into production. The hard part is not just writing tests, but determining if tests cover critical paths. When using standard coverage tools, coverage can seem convoluted and unrelated to how you write code. This is where Coverlet coverage comes in – a simple to use, open source library for measuring test file coverage, and improving test coverage.

If you've been writing anything more than "Hello world" programs, you are probably familiar with the concept of errors in programming. They are mistakes in your code, often referred to as "bugs", that cause a program to fail or behave unexpectedly. Unlike some languages, such as Go and Rust, where you are forced to interact with potential errors every step of the way, it's possible to get by without a coherent error handling strategy in JavaScript and Node.js.