Dealing with Fire (Part 2): How to Respond in a QA Crisis
You are halfway through a sprint demo when a teammate quietly flags something odd in staging. Minutes later, production logs confirm the issue is already live.
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Modern Software Development For Today's Systems & Applications
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.
Types Of Software Testing: A Comprehensive Guide (2026)
The types of software testing define how modern systems maintain stability, performance, and security in fast release cycles. In 2026, software is API-driven and continuously deployed, so testing is no longer a final step – it is embedded across the development lifecycle. Each testing type addresses specific risks and helps teams build a strong foundation of software testing instead of relying on random test cases. Let’s explore how these testing types work in practice.
Al boosts developer speed, so why does it slow testers down?
AI slows testers down when it’s added without a tester-first experience. Testers naturally question coverage and intent, so Katalon designs AI around real testing workflows to boost productivity instead of creating friction. — Alex Martins, VP of Strategy at Katalon Follow Katalon for more insights in our series!
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.
Testlio Accelerates Growth as AI Testing Demand Surges
Achievements include appointment of new CEO, the launch of LeoAI Engine suite, expanded partner ecosystem, and the addition of leading brands to global customer roster.
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.
Perforce 2026 State of DevOps Report Indicates Mature DevOps Practices Lead to AI Success
70% of organizations say DevOps maturity materially affects AI success.
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.