QASource Blog

Imagine using shared resources that are allocated dynamically, create flexible testing environments, and that simulate user scenarios and real-world traffic - that’s just some of the benefits of cloud testing.

Consider the internet like Pandora's Box. The internet has become so powerful because of data and data about data. For example, when you search the internet for something, you search for data about data. And a search proves to be useful only because someone preserved this information you were seeking somewhere over the internet. As technology advanced to support all this data, so too did the demand for big data applications.

Testers spend so many hours testing your web application to validate its functionality inside and outside of your local development environment. If your team relies on manual testing, your testers must enact and re-enact hundreds of test case scenarios across all essential browsers as well as record the issues and pinpoint the source of uncovered defects - all by hand.

Salesforce isn’t like every other CRM. In fact, many features and terminology are unique to the platform and are not applicable when testing other customer relationship management tools. If Salesforce user acceptance testing is so different, where does your team begin?

Every company wants the future of technology implemented today. That’s why the AI industry rapidly grows year after year and continues to be one of the biggest automation testing technologies trends in software testing. Adding machine learning and AI to your QA testing strategy can be both exciting and scary. It’s always fun to engage with new technology and discover all the key benefits of AI in QA test automation. But what impact does AI and ML bring to software QA? And should that change be embraced or rejected?

Congratulations on purchasing your LMS! Now comes your next challenge: implementing this learning management system into your organization. It’s true that integrating your new system with your other technologies is a critical process. Fortunately, it doesn’t have to be a daunting experience. In fact, you can expect impressive results when you have the right team and detailed strategy in place.

Within the development cycle, every team plays a key role. The software development team focuses on delivering code and the QA team focuses on product quality. With each team prioritizing a specific focus, going to market can only be a success - right? Not quite. Even with an issue-free product launch, the comradery levels across teams can be indifferent at best. In fact, many organizations would describe the relationship between developers and testers as a rivalry.

Software testing is a continuously evolving sphere. Often, testers only have hours to test a software and as a result, QA engineers tend to opt for automation and parallelization. Enter Docker containers. Dockers have revamped the way testing is integrated into the CI/CD pipeline: the multi-container testing approach eliminates time and resource-based bottlenecks.

Software development has been in existence for quite a long time now. However, the need for strong QA to complement the advancements of development has risen. With the increasing demand for high-quality products, it has become imperative for software companies to have strong QA in order to achieve development excellence.