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Markdown is a lightweight markup language widely known and used for formatting text on the web and has gained a lot of traction in the technical documentation side of IT. Many of the “README” documents people find when downloading software are written in or inspired by Markdown. When speaking in purely test automation form it is used to make your test case easier to understand and organize within the framework.
Have you ever heard of YAML- a weird name for some scripting language?
Well, if you are working within the software development industry and did not hear about it until now, you should probably keep reading this blog.
Since OpenAI came up with ChatGPT, rumors about the upcoming improvements of Artificial Intelligence are omnipresent. In this article, I want to discuss, if and how we can use chat-bots for software QA and Test Automation. Therefore I want to use ChatGPT. The tool is designed to give detailed answers to questions, using multiple Sources with the ability to summarize complex topics. Before I start to discuss how we can use this technology for Software QA, I want to point out how ChatGPT works. I am not an expert in the field so I had to ask someone who knows exactly what’s going on behind the scenes. I asked the only real expert within the field that I know and that is – you guessed it – ChatGPT itself.
For the Question of how ChatGPT works, I got a response that was a bit too long so I asked it to sum it up into two sentences. Here’s the response:
Right now, on the market there are a plethora of commercial and open-source no-code and low-code solutions available that can help organizations automate many of the tasks associated with QA (Quality Assurance) and improve the effectiveness and efficiency of testing. These tools offer a wide range of features, including AI-powered test case generation, test execution, and test management. By leveraging these tools, organizations can streamline their QA processes.
As we look towards 2023, we can expect to see a continued focus on improving the effectiveness and efficiency of QA (quality assurance) processes. One trend that is likely to gain traction in the coming year is the use of no-code and low-code solutions, driven by advances in AI technology.
As businesses continue to look for ways to stay competitive in today's fast-paced world, IT nearshoring has emerged as a viable solution. But what exactly is IT nearshoring and why should businesses consider it?
Let's go through some of the things that happened this year!
Testing? Making beer? They have one critical component in common. When done right, the results can be … Fantastic.
Initiating our first internal project at System Verification Germany
In these digital times, it’s all about new technologies, speeding up processes, gathering information easily, and managing our duties as fast as we can in just one click - anytime and everywhere we want. Since usability is stated as crucial for digital success, we are all experiencing its benefits and advantages.
Sounds great, doesn’t it? Well, not to everyone.
Due to disability, a large number of people are excluded from these advantages and thus, are excluded from our new digital society. Web Accessibility is not only necessary for about 30% of the people, but also part of human rights. Therefore, the EU enacted accessibility regulations: the EN 301459 including the Web Content Accessibility Guideline, which precisely states how to meet compliance with these regulations. The German government integrated this regulation and added 38 issues to the existing 60 WCAG guidelines in the BITV. Since these 98 aspects mentioned, cover a wide range of topics and we as a QA Company are driven by continuously improving software and expanding our knowledge, we decided to take the BITV test ourselves.
Performance Testing is a software testing process used to evaluate a software application's speed, response time, stability, reliability, scalability, and resource usage under the expected workload.
Performance tests are typically executed to examine speed, robustness, reliability, and application size. Performance testing goals include evaluating application output, processing speed, data transfer velocity, network bandwidth usage, maximum concurrent users, memory utilization, workload efficiency, and command response times.
Shortly, the goal of Performance Testing is not to find bugs but to eliminate performance bottlenecks.
