The best defense against unexpected failures is to build resilient services. Testing for resiliency enables teams to discover these failures before the customer notices. In my talk I’m going to present open source tool that can be used for containers resilience testing, stress testing, and network emulation, running on a Docker host or on a Kubernetes cluster.

Bugs are great learning opportunities. So how do we make sure we learn as much as possible from the bugs we find and fix? One way is to reflect on what made the bug hard to solve, and how we could avoid this type of bug in the future. For the past 15 years Henrik has written down short descriptions of the trickiest bugs he has solved. This simple method has helped him distill patterns that have influenced how he writes, tests and debugs code.

Even if your system is thoroughly tested and you are sure of its quality, customer acceptance is not necessarily a formality. In theory, the customer accepts the product after the acceptance tests, which at this stage of system development should not be a problem. So much theory, in practice, things can be different. So how to make sure that your product will successfully pass the business acceptance test? 

Have you ever been in one of the following situations while creating and using automated web tests?
– many scripting maintenances by changing data or elements on the front end
– flaky tests due to the waiting strategy or timings
– difficulty in having a coding pattern
– delay in running the tests, slowing the execution of your pipeline, resulting in a slow feedback

Myths say testers should only use TestNG when looking for an assertion framework. Myths say only developers use JUnit and that this framework is only suited for unit testing. Myths say a lot of things, but they are just myths.
The truth is both of these frameworks offer a lot of useful functionality for testers, whether they are ‘QA’ testers or ‘developer’ testers. 

As a research project to see why test automation of web applications is so hard, and why our Selenium scripts seem to break so frequently, we ran an experiment to analyze the top 500 (ranked by Moz) web sites to see what patterns we would find that could be optimized by either AI or ML. Unlike other presentation technologies, web applications present a uniquely difficult challenge for automation. They are written in a plain text markup language (HTML) that follows many conventions and rules (e.g. unique IDs, use class names for styling), but browsers are so forgiving, that many of the rules are ignored since they are not enforced in any way. 

If a good developer can write a bad code what is the guarantee that tester with no coding experience can write good code? Having a bigger team of testers who have their characteristic of writing code can be pretty painful when the tester will change the team or even worst leave the company. Maintenance is difficult even when the tester is still in the team since he has duplicated the same logic in a huge amount of page objects which will be almost impossible to be refactored in a very short period. Pattern Object Model helped us to gain the trust of new clients by delivering automated tests on day one on the project and regain the trust of existing clients by reducing the maintenance time.

Deliver business value with the right quality at speed. That’s what organizations ask of their IT teams. To achieve this, IT people need to work closely together. Cross-functional teams of business analysts, developers, testers, operations people, and other involved areas of expertise, join forces to work towards business objectives. Collaboration is key.

Continuous testing, continuous delivery, DevOps, digital transformations – these are all terms very popular in the last couple of years, and they all involve a shift in the way we deliver products, testing included! But when the product is providing automated financial advice or other financial services to their customers, the risk becomes a lot higher. So our first reaction is to be a lot more cautious before delivering it! But why?

Open Source testing tools have long dominated the test automation market, with millions of users leveraging the most popular frameworks such as Selenium and Appium. While these tools offer a promising array of features at a low price point, they often come with a number of new challenges that must be solved to achieve automation maturity. These challenges can surface both with teams looking to implement automation for the first time as well as teams transitioning from established legacy/closed source automation tools. In our experience with thousands of teams adopting open source for the first time, users will face challenges when it comes to: