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Rainforest

A Detailed Comparison of Cypress vs. Selenium vs. Katalon Studio vs. Rainforest

While Selenium IDE has been popular in the automated testing world, most teams using Selenium run into these problems. There are lots of different test automation tools—from easier ways to generate Selenium code to no-code SaaS (software as a service) options—all trying to solve these problems. In this article, we’ll talk about key differences between the following tools that represent the three main approaches to solving Selenium shortcomings.

8 Best Practices to Reduce Test Automation Maintenance

Even though automated testing helps you do more software testing in less time with fewer people, maintaining your test suite can be very time-consuming. Many QA teams have a hard time keeping up with maintenance as their product grows. If they fall behind, they get more and more false positives (i.e., cases where the test fails because of a problem with the test, not a problem with the application).

Software test automation is a competitive advantage. We're making it accessible to everyone.

Rainforest QA started in 2012 as a crowdsourced testing platform -- QA specialists from our worldwide community would follow plain English instructions to run customers’ test cases. After two years of development, we’ve now added a proprietary, no-code automation service to the platform, including a visual test editor anyone can use to create, update, and run complex, automated test cases without knowing any code.

How to Automate Regression Testing So Anyone Can Do It

Manual regression testing is time-consuming, costly, and difficult to scale as your team grows. As you add more features to your product, you have to hire more people and spend more time completing your regression test suite in every software release cycle. Automating your regression test suite can help your team scale up testing without adding more headcount.

The Snowplow Strategy: Improve Automation Test Coverage in Five Steps

In software testing, the term test coverage refers to how much of an application’s functionality is covered by test cases. In practice, the term also often refers to the effectiveness of that testing. QA teams use test coverage as a benchmark because it tends to correlate closely with the quality of the end product. Better test coverage typically means fewer bugs get shipped to production.