Systems | Development | Analytics | API | Testing

Automating QA testing helps ensure your website works flawlessly for every user, on every device, under every condition. From login flows to checkout carts, test automation gives teams the speed and confidence to ship frequently without breaking things. In this guide, you’ll learn what automated QA testing is, why it matters, which tests to automate, and how to build a reliable automated QA testing process from scratch.

This article first appeared on VentureBeat. Businesses know they can’t ignore artificial intelligence (AI)—but when it comes to building with it, the real questions aren’t What can AI do? It’s What can it do reliably? And more importantly, Where do we start? This post introduces the VISTA Framework, a structured approach to prioritizing AI opportunities.

Software development has never been more dynamic. With rising complexity, fast deployment cycles, and remote collaboration, developers now rely heavily on powerful tools to streamline their workflows. From writing and testing code to deploying and managing applications, the right set of tools can significantly boost productivity. In 2025, the integration of AI into developer tools is transforming how software is built.

The Patient Access API, introduced under CMS-9115-F, requires health plans, including Medicare Advantage, Medicaid, the Children’s Health Insurance Program (CHIP), and the Qualified Health Plan (QHP) on federally facilitated exchanges to give patients secure, real-time access to their health data via standardized APIs.

Did you know that 20% of API calls result in errors during SOAP to REST migrations? Poor error handling can lead to data loss, system failures, and degraded performance. Here's how to manage errors effectively during migration.

As part of our series on natural language query (NLQ), this blog details 5 benefits of using Guided NLQ, and how it differs from search-based NLQ to bring true self-service BI. Many analytics vendors today offer search-based NLQ tools. To explore data and find insights, you must use free text, but you also have to know what, or how to pose a query. The problem here is obvious: There is no guidance on what to ask your data, or how you can use the tool to ask questions and get helpful answers.

AI is becoming a crucial part of how we build software. From recommending products to helping businesses predict what their customers might need, AI is changing how we think about building and using apps and software’s. The wide variety of libraries and frameworks available in the Java ecosystem will bring developers powerful, specific tools for creating AI applications that enable a variety of subjects, including machine learning and natural language processing.

If you have the pleasure of working with a Rails app that uses a lot of data like logs, events, and metrics, you’ve probably run into performance issues at some point due to large tables. Deleting high quantities of rows can bring your database server to its knees or slow down queries to unacceptable latencies. PostgreSQL table partitioning is an excellent solution to these sorts of problems.

Mock data is the backbone of modern software development and testing. It allows developers to simulate real-world scenarios without relying on production data, ensuring security, efficiency, and reliability. Whether you’re testing APIs, building UIs, or stress-testing databases, mock data helps you isolate components, accelerate development, and catch bugs early.

Imagine you own a car. It’s reliable, runs smoothly and gets you where you need to go. But one day, you realize you need a GPS navigation system for better routes. What do you do? Would you redesign the entire car just to integrate GPS, or would you simply install a GPS device on the dashboard? Of course, the smarter choice is to add the GPS instead of modifying the car’s built-in system. This is exactly how a Kotlin Extension Function works.