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The latest News and Information on Software Testing and related technologies.

Performance Testing in Production

In this Blog Post we are going to discuss performance testing in production. Now before you think we have gone mad and lost our minds completely this is not as crazy as it sounds. Production is an environment that: All the things you spend a significant amount of time getting right in your performance testing environment and that can be difficult to achieve. Therefore, it seems like the perfect environment to performance test in.

Introducing Tricentis Test Automation for Salesforce, Test Management for Jira, and NeoLoad 9 with RealBrowser support

Today is an exciting today for us here at Tricentis! We’re introducing two brand new products: Test Automation for Salesforce and Test Management for Jira. We’re also releasing a major upgrade of NeoLoad for performance testing. Together, these new releases will enable customers to deliver new capabilities and workflows to their business faster, collaborate more efficiently among product teams, and enhance digital experiences for all end users.

What test cases should be automated (and which shouldn't)

Developing high-quality apps involves pressure to make tradeoffs on speed, quality, and features to meet deadlines for release. This tension between speed and quality comes to a head with QA: you need a functional product but can’t afford weeks of turnaround time. You can’t skip QA: the true cost of software bugs – the direct cost of mitigating the defects and the indirect cost of decreased consumer trust – is extraordinary.

Is Fortify Static Code Analyzer the Right Choice for Your Next SAST Tool?

There are many embedded systems out there, but only a few static code analysis tools that realistically support embedded software developers. The recent acquisition of Micro Focus by OpenText, including the Fortify Static Code Analyzer, reignites the question of which static code analysis tool is best for your embedded software project. Between Fortify and Klocwork, our experts have the answer.

Top 5 JavaScript Test Automation Frameworks in 2022

Chris Tozzi reviews the most popular JavaScript test automation frameworks and presents several things to consider as you select the best option for you and your organization. JavaScript consistently ranks as the world’s most popular programming language among developers. It should come as no surprise then that a variety of JavaScript test automation frameworks are available to help developers test JavaScript apps.

Introducing NeoLoad 9.0

Modern applications are constantly evolving, and with the advent of integrated DevOps toolchains applications can be built and deployed at ever-increasing velocities. This puts pressure on quality assurance teams to increase their velocity as well. With NeoLoad RealBrowser technology, we now offer a rapid way to record and immediately execute user paths to validate the performance of application builds as they move through their pipeline.

7 Top React Testing Libraries Everyone Should Know

In any application, testing is crucial, as it verifies that everything is working as expected and that what we are going to deliver to the end user is what was described in the project plan. Typically, it allows developers to inspect whether their app meets functional, performance, and UI specifications. Web applications can be tested using a variety of methods and types. These testing methods have already been combined into reusable libraries by many open-source developers.

The Selenium Click Command (Including Examples)

Learn how Selenium’s click() command works to simulate mouse clicks for automated UI testing, as well as how to send a right-click mouse command. If you’re using Selenium to automate UI testing for your app, Selenium’s will become one of your most commonly used methods. It’s important to understand how the Selenium click() command works for automated testing and how to find more information and resources when your needs are more complex.

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Load Testing: How Fast Can We Go?

Speedscale creates load tests from recorded traffic so generating load is pretty core to what we do. As a brief overview, we record traffic from your service in one environment and replay it in another, optionally increasing load several fold. During a replay the Speedscale load generator makes requests against the system under test (SUT), with the responses from external dependencies like APIs or a payment processor optionally mocked out for consistency. Your service is the SUT here. Currently the load generator runs as a single process, usually inside a pod in Kubernetes. So how fast is this thing, and how did we get to where we are today?