In the complex and rapidly evolving landscape of software development, the ability to make swift, well-informed decisions can be the dividing line between success and missed opportunity. As development cycles shrink and user demands grow, navigating the waters of software testing requires not just precision, but also clarity. This is where Katalon TestOps steps in with its game-changing feature: Virtual Data Analyst (VDA), powered by GPT technology.

We live in a highly interconnected world, and that interconnectedness couldn’t have existed without the tremendous contributions from the telecommunications industry. With 5G technology finally becoming mainstream, IoT growing at a rapid rate, and AI tech gaining prominence, the telecom industry is surely up for an exciting future. This faster-than-ever growth comes with the need for robust, continuous telecom testing to always maintain a high standard of service quality.

Application programming interfaces (APIs) serve as the backbone of today’s digital economy. They connect applications and web services with each other to exchange information and deliver thousands of digital experiences to users every day. With such significance, APIs can’t afford to be buggy, and software testers must frequently test them to identify and address potential issues. However, there’s a catch. Sometimes an API is not fully developed, or is simply too expensive to access.

API integration allows different software systems to connect with each other and exchange data seamlessly, and this process is literally the backbone of our digital world. While it is entirely possible to perform API integration manually, using dedicated API integration tools offer so many advantages to make this process more efficient, reliable, and manageable.

In the 21st century, data has become an invaluable asset that drives innovation, decision-making, and progress across various domains. Its importance stems from the fact that we are living in a digital age where almost every aspect of our lives generates, consumes, and relies on data. When it comes to software testing, data plays a crucial role to replicate positive/negative cases and identify corner or edge cases that might remain untested without conducting testing on various data values.

Robotic process automation (RPA) is a software system automation approach that employs pre-programmed “bots” to automate manual tasks, typically through a user interface (UI). RPA tools are primarily used to automate business processes that once depended on human resources and were highly repetitive and operational in nature. Many of these business processes are rooted in legacy technology, which often acts as a bottleneck due to its outdated nature.

What device should be used to run the tests? What operating system version, manufacturer and model to use? How to get these devices? These are some of the questions we ask ourselves when planning a mobile application testing strategy. If we consider automating these tests, other questions will surely come to mind.

In the fast-paced and highly regulated world of financial services, software quality is arguably of utmost importance. To ensure financial products meet complex requirements and deliver seamless user experiences, robust testing methods are crucial. One such approach that has gained significant traction in the financial industry is Behavior-Driven Development (BDD) testing.

The DevOps lifecycle is a set of continuous and collaborative practices that bridge the gap between software development and IT operations, promoting seamless integration, automation, and faster delivery of software. The DevOps lifecycle phases include.

Banking, financial service, and insurance (BFSI) applications are complex due to their heavily regulated nature. Beyond the commonly known test cases, QA teams must also consider industry-specific test scenarios to do BFSI testing well. This means that testers must equip themselves with two skill sets: testing knowledge and BFSI domain knowledge.