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

AI-powered testing, built for Jira: discover Sembi IQ

At Xray, powered by Sembi, we believe the next era of software quality will be shaped by intelligence, not just automation. Today, we're proud to introduce Sembi IQ, Sembi’s new AI platform built to help QA, development, and security teams deliver better software, faster. Sembi IQ is designed to work across the entire Sembi portfolio, including Xray, infusing intelligence into the tools teams rely on daily. This isn’t just an add-on or a buzzword-driven initiative.

G2 Summer Report: How Users Are Rating Katalon

The G2 Summer Report 2025 has arrived. Published by the renowned software review website g2.com, this report brings value to both sides of the market: With up to 37 G2 badges received this time, we're really happy to see that our product is resonating with users across a wide range of markets and industry segments, including DevOps, Software Testing, and Automation Testing. Here's a quick recap of the report.

Unit Testing Vs Functional Testing : Hands On Guide For Developers

To evaluate our software application’s quality and reliability we are going to have to test our application in a variety of ways. The two most basic forms of testing we have available to us are unit testing and functional testing. Unit testing and functional testing are the TRUE basic building blocks of those different types of testing.

Why We Built a Unified Error Monitoring Solution for Kotlin Multiplatform

The new bugsnag-kmp SDK is a unified error monitoring solution for Kotlin Multiplatform (KMP) projects, enabling developers to track and monitor errors across Android, iOS, and web platforms from a single codebase. The new SDK works seamlessly on Android, iOS, and web browsers Native Integration, each one linking directly with our existing platform SDKs.

What is Alpha Testing?

What’s the difference between a software launch that builds customer confidence and one that becomes a costly disaster? Often, it comes down to how thoroughly the product was tested internally before anyone outside the company ever saw it. he irony is that alpha testing is often the most cost-effective phase for catching serious issues, yet it’s frequently the first thing cut when timelines get tight.

Testing the Stream: A Deep Dive into QA & Release Engineering | Pramod Kumar | Ask Me Anything

Streaming platforms operate in a fast-paced, high-stakes environment where quality, reliability, and seamless user experience are non-negotiable. Ensuring smooth playback, handling high traffic surges, and maintaining low latency present unique challenges that require robust testing and release strategies. This session will explore the fundamentals of testing live and on-demand content, scaling automation, optimizing CI/CD pipelines, and ensuring stability across diverse devices and network conditions.

Sauce Labs Community Office Hours - Testing Libraries and Frameworks

Not sure which testing framework or library is right for your team? In this Sauce Labs Office Hours session, we’ll walk through how to evaluate popular testing frameworks—like Selenium, Cypress, and Playwright—and help you understand which one best aligns with your project needs, team skills, and long-term goals. Perfect for anyone new to automation or considering a change in tooling, this session will give you a clear starting point for making confident decisions in your testing strategy.

How To Reduce Regression Testing Time? 5 Actionable Strategies

Regression testing is indeed one of the most time-consuming part of software testing: repetitive, tedious, and requiring high volume of executions. And yet, you can't ignore regression testing. It is the guardrail preventing bugs from slipping into production. But if you don't try to reduce the time it takes to do regression testing, it becomes counter-productive, very soon.

Vibe-Coding Meets QA: What Happens When AI Writes 30% of Your Code?

With the rapid adoption of AI-driven coding tools, software development is experiencing a seismic shift. Increasingly, developers rely on tools like GitHub Copilot and other generative AI solutions (collectively termed “vibe-coding”) that now account for roughly 30% of code output in leading organizations. This trend raises significant questions for QA teams: What happens when AI significantly contributes to the codebase, and how does this reshape the landscape of software testing?