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By Opinov8, April 9, 2019



In software development, one of the most important — and time-consuming — tasks is software testing. To ensure a product functions properly before being released to the public, developers must carry out several different rounds of test execution, validation and reporting to highlight any areas that need repair or improvement.

Throughout the history of software development, test automation tools have existed to execute common workflows and assist developers in working on the kinks of their product. But these tools have often been cumbersome and expensive, requiring a knowledge of how to code that makes the tools difficult to set up. Many test automation tools also require a certain amount of manual testing, turning a seemingly automated process into a task that still requires human intervention.

The introduction of robotic process automation (RPA) tools has made software testing easier than ever before. Built to follow an automated workflow, RPA tools can be set to automatically carry out software testing on a wide scale without the need for human intervention. Using RPA tools can help teams greatly reduce the time spent carrying out boring and repetitive tasks, which can ultimately lead to human error. By following a structured, rules-based workflow, RPA tools can execute testing at greater efficiency than a human being, freeing up employees to focus on high-value tasks.



RPA tools typically require no programming skills, making it easy for non-technical users to establish a workflow for a digital worker to follow. When testing a user interface or API, the user equipped with RPA tools can simply build a workflow that doesn’t require additional work to carry out the automation. With the help of detailed analytics and reporting, RPA tools can be analyzed and adjusted to ensure testing is occurring thoroughly and accurately.

RPA tools are also incredibly useful for testing because they can be deployed across a wide range of platforms. Instead of having to find specific automation tools for particular operating systems or devices, RPA tools are often flexible and platform independent, supporting web-based, desktop and legacy application testing. Virtual machines through RPA tools also make it possible to scale testing at any time, saving resources while speeding up the testing process.

Many new RPA tools are beginning to employ artificial intelligence capabilities that can continuously improve upon its workflows. Rather than having to manually adjust a specific task, smart RPA tools can refine their behavior over time, making testing an automatic process that can be trusted to run without additional supervision.