Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
The latest News and Information on Software Testing and related technologies.
The Great Disconnect: Why 77% Confidence in AI Results Is a Major Business Risk
According to the Perforce 2026 State of DevOps report, 77% of organizations express high confidence in the outputs generated by their artificial intelligence systems. Yet, this widespread optimism masks a critical vulnerability. While executive confidence in AI results remains high, only 38% of organizations have embedded AI deeply across their delivery stages. Plus, only 39% maintain the fully automated audit trails required to verify these results.
Application integrity in the AI era | From the Bear Cave Ep. 3
The tsunami of AI-generated code creates downstream bottlenecks for QA teams, and shift-left or traditional test automation aren't enough in the AI era. In this From the Bear Cave session, SmartBear CEO Dan Faulkner and CMO Kelly Wenzel unpack how AI code generation impacts software quality and why traditional testing struggles to keep up.
Best Practices to Adopt for D365 F&O Automation Testing: How Top Retailers Are Winning with No-Code Automation
Are you still relying on manual testing for your Dynamics 365 Finance & Operations (D365 F&O) environment? In today’s fast-paced digital landscape, where Microsoft rolls out frequent updates and business needs evolve rapidly, manual testing is no longer just inefficient. It’s a strategic risk.
GDPR vs EU Data Act: Key Differences
Find out the key differences between GDPR (focused on data privacy) and the EU Data Act (focused on data ownership and portability). In this clip from the OpenLogic webinar, "Navigating EU Compliance: Open Source Strategies for Digital Sovereignty and Resilience", Perforce CISO Aaron Kiemele explains that contract clauses locking data into proprietary silos are now hard to enforce, and businesses must have credible, tested plans to exit a software platform if data policy or residency requirements shift.
Rust Language Support in Perforce Static Analysis Accelerates Secure, AI-Driven, Multi-Language Embedded Development Lifecycles
Single static analysis workflow catches critical errors beyond memory-safety for mixed-language systems, before defects are introduced during the coding phase of the development lifecycle.
Cloud Migration Strategies for Core Banking Platforms: A Practical Guide for CIOs
Most core banking systems were never designed to move. They were built to run reliably inside controlled environments, with tightly bound processes, batch cycles, and layers of regulatory logic stitched over time. Now, those same systems are expected to support real-time payments, embedded finance, and API-driven ecosystems, often without a fundamental redesign. That mismatch is forcing a shift.
In performance testing, AI's confidence can be your team's undoing
Quick summary: AI accelerates code creation, but its inherent confidence pushes structural risks downstream, where they surface as costly, release-blocking problems. As code output scales, performance validation that can’t keep pace becomes a headache and a business risk. Agentic performance testing embeds skepticism and performance awareness into the development process before risk can compound. Software development requires specialized expertise for a reason.
AI is writing your code. Is your regression testing keeping up?
AI is now writing more of your code than ever. But the problem is that your test suite was built to catch errors, not to catch the difference between what an AI agent produced and what your original specification actually required. As AI tools accelerate development velocity, the volume of code moving through pipelines is outpacing traditional quality processes.