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The latest News and Information on Software Testing and related technologies.

Reflect vision-based AI demo | Create one test for multiple platforms

Create a single mobile test that runs reliably on both iOS and Android - without building separate tests per platform or relying on brittle, platform-specific locators. In this high-level demo, we use SmartBear Reflect’s vision-based AI to record a typical workflow in a sample coffee app, where each step is backed by visual context and intent. Then we run the same test across a mix of Apple and Android devices, including an iPhone, to show how Reflect adapts to the environment at runtime and helps reduce flakiness and false positives.

Top Test Automation Best Practices Every Team Should Follow

Test automation has become an essential part of modern software development. In 2026, shipping fast without reliable test automation is almost impossible. Done right, it ensures consistent quality, faster feedback, and fewer production incidents. This guide covers practical test automation best practices used by real engineering teams to deliver measurable results.

Demystifying Data Virtualization: Why it Should Become One of Your DevOps Essentials

Data virtualization can help modern organizations solve the complex challenges that come with managing data. With information scattered across multiple systems, accessing data can lead to operational bottlenecks in your organization.

Maintaining compliance when adopting AI in regulated industries

Key Takeaway: Organizations in regulated industries can adopt AI without compromising compliance. Automated testing enables continuous validation of AI-enabled systems while maintaining the predictability, documentation, and audit-readiness that regulators require. In compliance-first industries, such as banking, healthcare, or telecommunications, AI adoption is rarely a simple technology decision. You are often caught between two competing pressures.

Why Python is Dominating High-Performance Computing

High-Performance Computing (HPC) has traditionally been an exclusive club. If you wanted to run massive simulations or crunch petabytes of data, you had to leverage the predominant languages used on supercomputing hardware—usually C, C++, or Fortran. Although fast and efficient, these languages demand strict memory management and complex syntax that require strong software development skills. Without them, development time can slow down significantly. But the landscape is shifting.

Unifying Data Masking and Synthetic Data for Test Data Management

Provisioning data for software testing requires balancing realism against security. Teams need production-like data to validate applications effectively. But they also have to adhere to strict privacy regulations. Two of the leading methods for creating and securing test data are data masking and synthetic data generation. Data masking de-identifies sensitive production data, preserving its scale, realism and referential integrity.

You've described Katalon as a hybrid testing platform. What does that really mean?

Calling Katalon a hybrid testing platform means it brings manual, automated, and AI-generated testing together in one unified system. Katalon is built to help teams design, run, manage, and report on all three types of tests side by side, giving clear visibility into coverage, quality, and release readiness without forcing teams to choose just one testing approach — Alex Martins, VP of Strategy at Katalon.