Why Test Maintenance is Killing Your Engineering Velocity (and How To Break the Cycle)
When testing debt piles up, it creates a quality ceiling that effectively stops your release velocity, regardless of how many developers you hire.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
The latest News and Information on Software Testing and related technologies.
10 Types Of API Testing Explained With Examples (2026)
APIs (Application Programming Interfaces) are the backbone of modern software; they let applications talk to each other, share data, and trigger actions across systems. Before any API goes live, it needs to be thoroughly tested to ensure it works correctly, handles edge cases, performs well under load, and stays secure. This guide covers all major types of API testing with real-world examples and tool recommendations.
Medical Practice Management Software: Features, Development Roadmap, Costs
Running a medical practice today involves much more than treating patients. Clinics must manage scheduling, insurance verification, billing, compliance, and reporting, often across multiple disconnected systems. When these workflows depend on manual processes or outdated tools, administrative work quickly overwhelms staff.
Best AI Test Case Generators for QA Teams in 2026
AI test case generators are spreading across QA teams, with Gartner predicting that 80% of engineers will need to upskill by 2027. Prioritize platforms that unify AI test generation with test management rather than tools that fragment your QA workflow.
How to scale API standards across large teams | Swagger Studio
When multiple designers and teams contribute APIs, you face inconsistent schemas, divergent patterns, and broken assumptions. However, the "shift-left" approach to API standardization helps you catch issues early, automate compliance, and maintain quality without manual gating – making your API program truly scalable. In this video, SmartBear Senior Solution Engineer Joe Joyce demonstrates how to enforce consistent API standards across large development teams using Swagger Studio's governance, collaboration, and CI/CD integration features.
LLM Output Evaluation & Hallucination Detection
As enterprises transition from experimenting with Generative AI (GenAI) to deploying Large Language Models (LLMs) in production, a critical challenge has emerged: reliability. While LLMs demonstrate remarkable proficiency in automating workflows from drafting executive communications to summarizing complex legal corpora, their susceptibility to "hallucinations" remains a significant operational risk. The scale of this challenge is non-trivial.
How does BearQ autonomous QA work? Your top questions answered
Testing software at scale has always been a race against change. Then, AI-coding turned what was once a challenge into a crisis: rapid development cycles accelerated by AI have made it impossible to maintain comprehensive test coverage and catch issues before they impact users. In SmartBear’s Closing the AI Software Quality Gap Study, 60% of software experts told us they experienced quality issues as development outpaces testing.
When Your Observability Literally Stops Traffic
Last week, a fleet of autonomous robotaxis in China suddenly stopped working—at scale. Over a hundred vehicles stalled across a city, stranding passengers in traffic and raising immediate concerns about safety, reliability, and trust in autonomous systems. This wasn’t just a bad day for self-driving cars. It was a distributed systems failure, one that happened in the physical world, not just in dashboards.
OpenTelemetry Trace Testing for CI Release Gates
OpenTelemetry is great at answering one question: “what just broke?” The problem is that most teams need a different answer first: “what is about to break in this release?” That is where trace-based testing comes in, especially for teams running a vendor-neutral OTel stack (Collector + Tempo/Jaeger + Prometheus) and needing deterministic release gates.