Systems | Development | Analytics | API | Testing

In today’s fast-paced software development landscape, the demand for high-quality applications is at an all-time high. As organizations increasingly rely on Oracle technologies for their critical business operations, ensuring the reliability and performance of these systems is paramount. One of the most effective ways to achieve this is through automated testing.

In today’s rapidly evolving digital environment, organisations face mounting pressure to make strategic technology investments that deliver immediate operational benefits and long-term competitive advantages. As businesses navigate this landscape, iPaaS has emerged as a transformative solution that addresses complex integration challenges while delivering substantial returns on investment.

Ever written an automated test, only to have it fail the following day because the 'Submit' button changed its class name? Frustrating, I'm sure. Why are UI tests so flaky and why are selectors so flaky? Testers use CSS classes or IDs. Every time they see them, the class or ID changes every time the developers build the code. It makes automation brittle and long to update, especially due to the deep nesting and dynamic DOM elements. However, what if there was a more efficient way?

Nowadays, Agile and DevOps practices demand rapid iterations and continuous testing to ensure software quality. Manual testing alone can’t keep up with this speed, making test automation important to continue delivering high-quality products at a rapid rate. Despite its advantages, test automation isn’t as simple as writing and running a few scripts.

Quality Assurance (QA) leads ensure that automated testing contributes to delivering high-quality products. But how do you measure the success of your automation efforts? This is where tracking the right metrics becomes essential. Automation metrics provide QA leads with insights into the efficiency, reliability, and impact of their testing strategies. When used effectively, these metrics can identify bottlenecks, guide decision-making, and improve overall team performance.

Modern software applications demand rapid delivery, continuous integration, and cross-platform compatibility, particularly when the software experience itself is the product.