We did a sort of time travel on 20th April at QonfX. If you are not one of the 3000+ people who registered for this event, it is a unique software testing conference that keeps its focus on the Future of Testing. This year was the second edition of QonfX and received even more love than the last time. Feedback like the above filled our social feeds during and post QonfX. We cannot keep a count of the number of times attendees used the words ‘eye-opening’ for the talks given by the speakers.

Businesses increasingly rely on digital technologies to streamline operations, enhance efficiency, and stay competitive. However, with the advantages of digitization come inherent risks and challenges that can disrupt business operations. Recognizing the need for a comprehensive framework to address digital operational resilience, governments worldwide have introduced legislative measures to safeguard businesses and consumers.

Any (functioning) system is built upon an infrastructure. This infrastructure supports all of the functions and activities of the system. Testing is no exception. With a good test infrastructure, QA teams can speed up their testing efforts and drastically improve efficiency. In this article, we will explore the concept of test infrastructure, and how you can effectively build one.

At the end of every testing project, a test report is usually created to summarize the results. This report provides insights into how the test project was executed if it aligned with the initial plan, and what areas need further optimization. In this article, we’ll explore in-depth what needs to be included in a test report, as well as the key metrics that QA teams need to look at if they want to gauge their testing efficiency.

Kernighan & Pike, The Practice of Programming, 1999 Despite constantly changing technologies and the needs of customers, some wisdom seems eternal. Programmers need to test their code. But thorough testing takes time. When we do it well, everything works, and a massive testing effort feels like a waste. However, when we do it badly, our code is often broken, and we wish that we had done better testing. I have some good news for you.

This blog post is designed as a guide to illuminate the critical importance of software testing plans—a cornerstone in ensuring the delivery of reliable and high-quality software products as we described in a previous post when we described the process of creating a complete Test Plan. For QA professionals and testers, as well as for those developers that are getting initiated on a journey into the world of testing, this post serves as a reaffirmation of our principles.

As software systems become increasingly complex, observability — the ability to understand a system's internal state based on its external outputs — has become a critical practice for developers and operations teams. Traditional observability approaches struggle to keep up with the scale and complexity of modern applications. As the amount of telemetry data grows, it becomes expensive and complex to navigate. Enter AI and its promise to revolutionize observability.

Brace yourself for a two-month special of all things new in Loadero that were introduced in the months of March and April! Deprecation warning for Loadero API: after 01.07.2024. participant and run_participant responses will no longer contain a “media_type” field. If your usage of Loadero is dependent on the expectation that this field will be present, then we suggest removing this dependency in the near future.

The world of Dynamics 365 is constantly changing, and staying on top of those changes is crucial for any organization that uses it. The arrival of April 2024 brings with it a significant update, including the much-anticipated one-version rule. This has sent a wave through the Dynamics 365 community, with businesses scrambling to update and ensure compliance. While the one-version rule is a major change, some stakeholders may not yet fully grasp the impact it will have.

QA engineers and developers constantly worry that new updates will hinder the functionality of their applications. Regression testing tools prevent this and ensure that applications run smoothly after a code update. Most QA teams use automated regression testing software to save time and money while speeding up the release cycle. However, these benefits only apply when you use a web testing tool that suits your use cases.