The latest News and Information on Software Testing and related technologies.
From the traditional Waterfall model to more iterative approaches like Agile and DevOps, software testing is constantly evolving. And while teams have worked their way to deliver quality at speed, there seems to be something holding them back. Read on to learn about in-sprint automation and why it’s the key to moving at DevOps speed.
One of the most important aspects of automated web application testing is having a good grasp of using locators. Locators allow retrieving DOM elements from the web page. Interacting with web elements during automated tests allows to create end-to-end tests that simulate real users behavior. In this blog post, we will talk about two types of locators – CSS selectors and XPath.
Manually testing an application is time-consuming, costly, and difficult to scale as your application grows: as you add more features to your application, you have to add more functional tests. And getting those additional tests done usually means adding headcount. Automated functional testing can speed up the testing process, provide more consistent results, and give one person the ability to manage the testing workload of five or more manual testers.
If you're looking to scale up your manual software testing without hiring a whole team of in-house testers, there are several outsourced software testing services that use crowd testers to provide affordable results. Many of these providers look similar on the surface—most offer exploratory testing, some version of scripted testing, and claim to integrate into your team's workflow.
Flaky tests are like meme stocks — many people have them, but no one knows what to do with them. Today, we will change that by diving into some common causes and, more importantly, solutions for flickering tests in Elixir. Elixir has many great primitives that let us run tests asynchronously, including immutable data, lightweight processes, and the Ecto SQL sandbox. Running tests asynchronously can greatly speed up your test suite, but can also increase the chance of flaky tests.
Testing and Quality Assurance can be endless tasks. That’s why testing teams need metrics to measure and quantify their work and success. Testing metrics provide tangible ways to measure the progress of testing, as well as the readiness to deploy a product. One of the most common and useful metrics is code coverage. Many testers consider it a good practice to write test cases that provide maximum code coverage and verify the expected and wanted behavior of the software.