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

Comprehensive AI Security Testing for Enterprises

Enterprise QA teams are discovering that deploying machine learning models breaks their existing validation pipelines. Legacy testing environments rely on a simple truth: fixed inputs must produce predictable outputs. Because intelligent architectures operate on probabilistic distributions, deterministic testing alone can no longer guarantee reliability. When conducting a code review or architectural risk assessment, treating an active model as a standard black-box API leaves critical flaws unaddressed.

Katalon Product Roundup June 2026

June's releases share one thread: less setup between what you already know and a working test. Production Insights can turn a single real user session into a test case without a full Journey Map first. Katalon AI Assistant now reads the docs and boards your team already works in, shows its reasoning as it goes, and reaches apps your CI never could. Test management got safer to run at scale, with version history, ALM sync, and encrypted secrets. Here's everything that shipped.

The Reason Your Tests Are Flaky And How to Fix It Using Keploy

Ever had an API test fail even though nothing in your code actually changed? That's a noisy field problem and it's one of the most common causes of flaky tests. In this video, we break down: If you're tired of re-running tests just because a timestamp didn't match, this one's for you. Timestamps.

How to Monitor Your MCP Server (Step-by-Step Guide)

MCP servers have quietly become production infrastructure. If you have shipped a Model Context Protocol server so that Claude, an agent, or a connector can call your tools, that endpoint is now on the critical path. When it goes down, or starts returning errors, your users feel it the same way they would feel any API outage. The difference is that most teams are not watching it yet.

Securing Non-Deterministic Systems: Comprehensive AI Security Testing for Enterprises

Enterprise QA teams are discovering that deploying machine learning models breaks their existing validation pipelines. Legacy testing environments rely on a simple truth: fixed inputs must produce predictable outputs. Because intelligent architectures operate on probabilistic distributions, deterministic testing alone can no longer guarantee reliability. When conducting a code review or architectural risk assessment, treating an active model as a standard black-box API leaves critical flaws unaddressed.

Tosca's AI is coming to on-premises deployments this fall

This fall, Tosca’s suite of AI capabilities will be available for on-premises deployments — giving teams the tools to meet the pressure of the AI era head-on. Customers will gain access to leading AI features, including Agentic Test Automation, AI-powered test creation, MCP connectivity, and AI Workspace, no matter their deployment type or existing infrastructure. AI’s unprecedented development means testing practices that were standard a year ago could already be outdated.

How to Accelerate Vulnerability Remediation with AI

Perforce QAC and Klocwork's new AI-assisted code remediation capabilities combine deep static analysis with AI-guided fix recommendations, helping developers resolve issues faster while maintaining compliance, security, and code quality. In this webinar, you'll see a live demo of how teams can accelerate remediation, reduce rework, and enable flexible AI-powered workflows directly within their development environment.