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

Siri 2.0 Delay: Testing Gaps That Just Cost Apple 6 Months

The news dropped this week, and it sent shockwaves through the tech industry. Apple has officially pushed back the release of its highly anticipated Sir i 2.0. Reports from Bloomberg indicate that the update, originally slated for iOS 26.4, ran into severe hurdles during internal review. The culprit wasn't a lack of innovation or features. It was a failure in quality assurance.

Celebrating Datalex: Setting the standard for developer visibility in API-first development

At SmartBear, we recognize organizations that improve software quality by increasing clarity, alignment, and confidence across the development lifecycle with the Developer Visibility Award. For 2025, the award goes to Datalex, a leading airline e-commerce solutions provider. Datalex equips airlines with API-driven platforms that provide tools for driving revenue and profit as digital retailers.

Why Your Company Will Be Running OpenClaw Next Year

You’ve probably heard of OpenClaw. Maybe you’ve seen the demos where an AI agent opens a browser, navigates to your CRM, fills in a form, and files a support ticket. No API required. Maybe you thought “that’s cool but I’d never run that at work.” Your employees already are. According to Permiso’s research, 22% of enterprise customers have employees running OpenClaw without IT approval.

How AI Coding Is Breaking Synthetic Data Generation

Traditional synthetic data generation approaches, still called “Test Data Management” (TDM) by legacy vendor, were designed for a world where applications were monolithic, databases were the center of gravity and change happened slowly. The world looks a lot different now. Modern systems are distributed, often times event-driven, and increasingly powered by streaming data and AI agents. In this environment, batch-oriented synthetic data generation fails to capture how systems actually behave.

DLP, Traffic Replay, and the Missing Link to Software Quality

In Part 1 and Part 2 we explored why testing modern software is so difficult. Production data is the most valuable input for testing, but it’s locked away because it contains PII and sensitive context. Traditional Synthetic Data Generation (SDG) was built for batch databases, not streaming systems. And AI coding agents amplify every weakness in existing test strategies because they need current, realistic data or they generate buggy code based on outdated assumptions.

5 Lessons learned building a web application crawler

Building a web application crawler came with plenty of challenges—here’s what we learned. Recently, we built a web application crawler from scratch—which had some scratching their heads, asking why we’d undertake such a thing. Here’s our answer to that, plus some interesting technical challenges we ran into and how we tackled them.

4 Steps to Take Back Control of Your Java Release Cycle and Manage Dependencies Better

Regaining control of your Java release cycle can dramatically improve build stability, security, and developer productivity. In this video, Perforce OpenLogic experts share practical guidance on Java dependency management, including how to audit dependencies, govern their use, and reduce risk in complex builds.

Navigating Spring Dependencies (Spring Boot and Framework)

Navigating Spring dependencies can be challenging. As many Java developers know all too well, the biggest risk in maintaining legacy Spring applications isn’t in the code you wrote — it’s in the web of dependencies you inherited. Hidden deep in your build files, these libraries can make or break your application’s ability to stay secure and up to date. In this video, OpenLogic experts explain how transitive dependencies in older versions of Spring Boot and Spring Framework can negatively impact your application's stability and security.

State Transition Testing: Diagrams, Tables & Examples

Ever seen a workflow pass QA, then fail the moment users retry, refresh, or hit a timeout? That gap usually isn’t about a “wrong input.” It’s often because the system is in a different state when the same input arrives. In state transition in software testing, the state decides what’s allowed, what must be blocked, and what should happen next. It is one of the simplest ways to make these workflows behave predictably in the real world.