Load testing is a big category, and how do you even start preparing for it? This post covers it all from planning to implementation.

As the software development industry continues to evolve and become increasingly complex, organizations must find new ways to streamline their testing processes. Low-code test automation comes into play here. These platforms provide an efficient and cost-effective solution to test automation, empowering engineering teams to create and execute test scripts without extensive programming knowledge.

An application has different Web Elements like buttons, text boxes, checkboxes, menus, sliders, and more. While testing using Selenium, you can simulate certain scenarios by automating low-level interactions with the WebElement(s) in the DOM, such as keypresses and mouse button operations (such as click, double click, and right-click). One such action is Mouse hover over a web element. Moving the cursor over an element in a graphical user interface (GUI) without clicking is called hovering.

The main goal of performance testing is to measure the application's response time, throughput, resource utilization, and other relevant metrics under different loads and stress levels. It can be regarded as a kind of software testing that varies between different user loads. Performance testing can be used to identify and isolate performance bottlenecks, optimize system performance, and ensure that an application or system meets its performance requirements.

The best description of untrusted data I’ve ever heard is, “We all attend the QBR – Sales, Marketing, Finance – and present quarterly results, except the Sales reports and numbers don’t match Marketing numbers and neither match Finance reports. We argue about where the numbers came from, then after 45 minutes of digging for common ground, we chuck our shovels and abandon the call in disgust.” How would you go about fixing that situation?

Discover the benefits of design patterns, how Laravel uses the manager pattern, and how you can use it too!

The insurance industry has always been one of the most data-intensive industries. With a large amount of customer data, claims data, and other information, insurers have been adopting artificial intelligence (AI) to streamline their processes and provide better customer experiences. AI-powered technologies have enabled insurers to automate claims processing, fraud detection, and underwriting, among other things. Here are six top use cases of AI for insurance.

In Part 1 of this series about Test Case Design, you learned that by using the Test Case Designer tool in Xray Enterprise, you take a model-first approach to designing more thorough and efficient tests. But how does the tool generate optimized scenarios once we define those models? And what do we mean by “optimized”?

In today’s digital age, security has become a top priority for businesses of all sizes. With the increasing number of cyber-attacks and data breaches, ensuring that your website and applications are secure is essential. Usually, access to websites that are actively being developed or are intended for private/internal usage within an organization is restricted. A common way to do this is with custom SSL certificates. This ensures that the website won’t be publicly available.

Apache Airflow and dbt are both popular contenders for the best workflow management tool in the Modern Data Stack. However, when it comes to picking the best tool, the differences are not trivial, and the use cases for each tool are quite different. In this article, we’ll compare dbt vs Airflow on multiple points.