Systems | Development | Analytics | API | Testing

In Selenium test automation, managing test scripts efficiently is important for improved scalability, readability, and maintainability. The Project Object Model (POM) is a design pattern that improves the structure of automation scripts by creating a separate class for each web page in an application. Page Factory is a more advanced version of POM that further simplifies object repository management.

JavaScriptExecutor executes JavaScript code directly within the browser. Using JavaScriptExecutor in Selenium, testers can perform advanced automation tasks like scrolling, clicking hidden elements, handling alerts, and manipulating the Document Object Model (DOM). This makes it an important tool for improving browser testing features. Read further to learn more about the basics of JavaScriptExecutor in Selenium, their use cases, working methods, benefits, etc.

Yassir decided to consolidate our data infrastructure with Google Cloud to bring all its storage and analytics functions into one place.

Choosing the right API architecture is crucial for building efficient and scalable applications and the two prominent contenders in this arena are GraphQL and REST, each with its unique set of characteristics and benefits. Understanding the similarities and differences between these two approaches can help teams make informed decisions when designing APIs. This article aims to provide a comprehensive comparison of GraphQL and REST, highlighting their key features, advantages, and use cases.

In Android, ImageView is a widget used to show an image, so it’s vital for every kind of app we build. In fact, it’s the most common widget that we’ll use as Android developers. The image can be a profile image, graphic, or any other type of image, and it can be loaded from a res/drawable folder or an external source. ImageView is pretty straightforward once you’ve got the hang of it, but there’s some stuff we need to know if we’re going to make the most of the widget.

Some 70% of organizations are actively exploring or implementing large language model (LLM) use cases, but fewer than a third of generative AI experiments have made it into production. A common hurdle? The inability to access and leverage the data crucial for running AI applications effectively. Snowflake’s Accelerate 2025 virtual events dive into the challenges and myriad opportunities offered by AI.

The PropTech market is more competitive than ever. More than 5,000 real estate SaaS companies are fighting for market share, with $9.35 billion in funding backing 1,000 of them. But funding alone doesn’t guarantee success. Plenty of well-funded SaaS platforms often fail to scale, integrate, or secure their data properly. Instead of improving operations, they create bottlenecks, inefficiencies, and frustrated users. So, what makes SaaS for PropTech truly effective?

In Java “an event that occurs during the execution of a program that disrupts the normal flow of instructions” is called an exception. This is generally an unexpected or unwanted event which can occur either at compile-time or run-time in application code. Java exceptions can be of several types and all exception types are organized in a fundamental hierarchy. Understanding this hierarchy is crucial for implementing robust error handling strategies in production.

Imagine spending months developing a C++ application, only to have users report that it crashes whenever they enter unexpected input or when network connections fail. This common scenario happens when programs lack proper error handling. The good news is that C++ provides a built-in mechanism called exceptions that helps your code anticipate and respond to problems rather than simply crashing.

APIs have become the backbone of our digital world, with surveys showing that over 70% of developers plan to increase API usage year-over-year. They power everything from mobile apps and SaaS integrations to IoT devices and partner platforms, enabling businesses to deliver seamless services and experiences to customers. As organizations grow, however, so does the complexity of their API ecosystem.