QASource Blog

"You can't improve what you don't measure" - this saying is rightfully true for the world of software quality assurance. Quality Assurance (QA) metrics are used to estimate the progress and outcome of test results. Through metrics, it is easy to track the status of QA activities, measure team efficiency, and optimize processes.

Blockchain is not only a rapidly evolving technology but also a complex innovation that is now getting heavily integrated with different systems and being utilized extensively. It is used most primarily for cryptocurrency transactions.

Smart contracts are being adopted at an increasing rate. They have the potential to change everything from how we use money to how we vote and even do business transactions. Smart contract platforms like Ethereum allow developers to create applications that can become self-enforcing agreements between two or more parties. This means that once a smart contract is created, it will execute automatically when all of the conditions within the contract are met without any need for human intervention.

The innovation we know as blockchain is one of the most significant inventions in the 21st century. Its technology has become so popular that it has generated a domino effect that has affected many sectors such as healthcare and manufacturing.

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.

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.