QASource Blog

As technology rapidly advances and constantly improves, so too must the development practices that create these digital experiences for customers. Because the demand is not slowing down, more and more companies are transitioning their IT practices towards adopting a DevOps culture. With DevOps in place, businesses can better streamline the development, testing, management and deployment of software products to exceed customer expectations. DevOps provides the solution that many organizations need, however, it is not something that can be turned on with a flip of a switch. DevOps requires full understanding of procedure standardization, workflow management and automated testing before adopting this development methodology. For example, what is DevOps in software testing? How has DevOps changed software testing? And what are the pros and cons of software testing in DevOps? Our guide to software testing in a DevOps culture answers your most pressing questions so that you can decide if DevOps is right for you.

With every new release, smartphones are adding new features to their reservoirs. While the apps are doing what they do best, any distraction from their regular functions can lead to an interruption.

Every QA engineer can agree that API testing tools are very important when overcoming the common challenges that API testing presents. Yet strong opinions surface when debating which is the best tool to use when following API testing automation best practices. The solution is simple - choose the API testing tool that fits the specific needs of your product, your team and your development cycle. Yet the question remains the same - which API testing tool is the best fit for your product? There’s a lot we need to unpack before you can make this decision. What are API testing tools? How should your team choose an API tool? And is there an API testing tool list that can streamline this decision-making process? We compiled this API testing tool comparison so that your team can expedite your decision based on facts, not hype.

There’s a world of difference between “good” and “good enough.” Think of it in end-user terms—what sort of emotional response are you hoping for when your customers get their hands on your product for the first time? You want them to be impressed, at ease and to have the best experience possible. You don’t launch a new product, or upgrade an existing one, with the intention of your customers eventually getting the hang of it after a few trial and error moments. That’s the difference between “good” and “good enough,” and it’s what ultimately leads to success—or failure. Achieving that difference is what your QA process should be all about.

There are more than just technical aspects when it comes to launching a streamlined QA process. You must also stabilize the communication and workflows of both your internal and external teams. Our team of experienced QA engineers have put together a comprehensive QA checklist. These strategical steps will assist you from initial internal planning through to the final stages of test execution and release.

Blockchain applications are not like most applications on the market. While the performance, functionality and user experience of a blockchain application often parallels other applications, the structure of its data system adds another level of complexity when it comes to QA testing. So much so that it requires particular tests to be performed, specific tools to aid the testing process and specialized skills for your QA testers to acquire. But what is blockchain testing? What is blockchain used for? Why is it important to perform blockchain QA testing? And how does somebody start to test blockchain applications? This tutorial aims to answer your most pressing questions about blockchain testing so that your QA team can fully understand and properly test your blockchain application.

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?

QA managers are tasked with continuously finding ways to improve quality assurance and overall software integrity, but are also asked to find ways to increase productivity of team members. But, between rounds of testing and writing up issue reports, there never seems to be enough time to carry out these changes. Increasing productivity of your QA team doesn’t have to be difficult. Targeting easy wins allows for more time to implement additional tactics that improve team productivity. And since there are a lot of tasks that QA teams tackle, increasing QA productivity can help successfully drive a company’s revenue growth. Here are 6 ways to increase productivity within your QA testing team:

Think of HITECH compliance like a HIPAA upgrade. The HITECH Act came more than ten years after HIPAA in order to enforce tougher data security requirements mandated for all healthcare organizations as well as their business associates to follow. But what is the HITECH Act? What is HITECH compliance? And what software testing strategies should your team implement in order to uphold HITECH compliance?