Systems | Development | Analytics | API | Testing

Organizations relying on testing tools from Micro Focus (and before that, HPE) to ensure the quality of their digital initiatives recently received sobering—if not surprising—news: Micro Focus announced that it was being acquired by OpenText, giving the company’s aging testing products their second “new home” in five years (Micro Focus acquired ALM/Quality Center, UFT, and LoadRunner as part of their 2017 purchase of HPE’s software business).

At some point, every software engineer will find themselves in a situation where they need to benchmark system performance and test the limits of what a given system can handle. This is a common problem in software engineering, and even more so in the applications that are well suited for Elixir. Finding bottlenecks early on in an application can save a lot of time, money, and effort in the long run, and give developers confidence in the upper limit of a system.

Great software engineers are expensive, in-demand, and incredibly hard to find. Building an engineering team is a heroic feat – but stop asking them to moonlight as testers and build a QA team instead. Trying to offload QA duties onto your engineers is not as effective as you might hope. Unhappy developers lead to high turnover, slower release time, and an expensive talent search. Take it from the experts; build a QA team if you want high-quality products and releases.

Regression testing and unit testing are two different types of testing, yet many of TestQuality users use them interchangeably. Although we already went through Regression Testing Challenges and Best Practices in a previous post, it's important to distinguish between the similarities and differences between regression testing and unit testing. All unit tests are, in essence, regression tests.

Testing is the bottleneck of devops. 80% of testing is done manually. This is time-consuming, error-prone, tedious, and expensive. It's a hundred times more expensive to fix an error caught in production versus an error caught. Dev teams are being pushed to release code faster, release new features faster, and beat their competitors in every possible way. Automation is a cheaper and more accurate way to test. It lets everyone focus on most important goals.

In this post we are going to look at performance testing on large scale programmes. A few the posts we write define techniques and approaches based on a single application under test but sometimes you are faced with the prospect of performance testing: Now, especially in the case of migration of services, performance is key, and you cannot afford to see a degradation in performance as the business users will have already become accustomed to the software and how it performs.

Maintaining physical devices can be costly, risky, and unsustainable in a way that negatively affects mobile app release cycles – and your bottom line. Learn why a real device testing cloud can help improve both the customer experience and the developer experience.

The future is mobile. Maybe it would be more accurate to say the present is mobile. With 7.26 billion smartphones in the world, it’s not difficult to see why there has been such rapid growth in mobile app development over the past couple of years. When there is almost one mobile device per person on Earth, it becomes clear that this is an enormous market with seemingly limitless potential. Sauce Labs recently completed our 5 billionth test, a huge milestone and a number we are proud of for sure.