A healthy QA culture results in strong, confident teams. And with a powerful team in place, you can produce exceptional products and achieve greater success when going to the market. While the task of building great culture belongs to the QA Team Manager, it’s up to each member of your software QA team to participate and contribute towards a healthy workplace culture.
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.
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?
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.
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.
We are in an open-source revolution, an era where engineers and developers around the globe can collaborate and invest their time and money with the goal of producing a reliable product – a software that would further push the world toward digital innovation. Because of this common end goal, open source tools are gaining popularity in developer communities and more are turning toward adopting open source tools to build their product.
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.
The Agile testing environment creates strength in numbers. It aligns the talents and vision of your entire team to ensure the promise of your product becomes a market reality.
Every stakeholder in your software development life cycle is involved from beginning to end. You can maintain an end-user focus through the development and analysis of daily builds using a cyclical, continuous integration model.
The internet today is like Pandora's Box. The question here is, "How did the Internet become so powerful?" The answer is with data, and data about data. When you search the internet for something, you are searching data about data. Those searches provide us with useful information only because someone has preserved this information somewhere over the internet, and as this technology advanced, the demand for Big data applications was created.