Systems | Development | Analytics | API | Testing

Automotive infotainment systems are a core component of the modern driving experience. As these systems expand in features and complexity, the challenges for the software design teams behind them also increase. For automotive leaders, designers, and technicians, staying ahead means.

SmartBear participated in and won first prize at the ALMathon, the annual hackathon for SAP Partners. The challenge: Create innovative use cases to extend SAP Cloud ALM. So, we integrated Reflect, our AI-powered test automation product, into SAP Cloud ALM to enable users to automate their manual testing process.

With Xcode 26, Apple has finally introduced Xcode Compilation Caching: a major leap forward for iOS developers, who no longer have to wait around for slow builds while their CI pipelines recompile code that hasn’t changed. At Bitrise, our Build Cache product already supports Bazel and Gradle, so the logical next step was to introduce support for compilation caching in Xcode. In this blog post, we’re lifting the hood on how we built this new feature.

Three out of four software leaders think agentic AI will be fully trusted for autonomous testing by 2027, yet only nine percent completely trust AI today. Let’s unpack the data and see what the trust gap tells us about the journey ahead.

It doesn’t matter if you’ve got a team of human QA testers or you’re using one of the many automated testing solutions out there, the truth is this: if you have poor data seeding your QA strategy is going to suffer tremendously. If you do it properly, it enables you to run your whole test suite concurrently, keep your tests focused on the actual functionality they should be testing, and make maintenance easier.

Why do some QA teams consistently deliver reliable and high-quality software, while others toil to identify bugs and experience unstable releases? The real difference often is related to how easily the team is able to use software testing metrics to make measurable decisions. Often, the testing process turns out to be a routine checklist activity – run the tests, publish the results, and move on. However, without useful test metrics, the QA teams simply keep guessing.

Data integration logging is the process of recording events and activities during data movement across systems, ensuring accuracy, troubleshooting, and regulatory compliance. In complex environments like those of Netflix and Airbnb, logging is critical for system reliability and performance. However, challenges such as managing large log volumes, inconsistent formats, and compliance requirements make effective logging difficult.

AI is evolving faster than the guardrails meant to validate it, leaving organizations exposed to compliance risk, model drift, opaque decision paths, and breakdowns in trust.

In 2025, as AI models increasingly generate, refactor, and deploy code on their own, developers face a new challenge: how to safely run code they didn’t write. Sandboxes have become the backbone of this new workflow because they are lightweight, secure environments that let teams test, validate, and monitor code without risking production systems.

Getting the right answer to a technical question, right when you need it, can be the difference between a minor speedbump and a major roadblock. We all know the feeling of being stuck on a specific error or needing a quick "how-to" guide to keep a project moving. That's why we’re excited to announce that the new 24/7 Katalon Support Assistant is now live in production! It's an AI-powered technical support agent and the fastest way to get the help you need, anytime.