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Information Loss in Software Testing The higher you climb in the organization, the less information you get: An executive might only see red, yellow, and green for a project. Any time different teams need to communicate complex information, there is bound to be some information loss, and maybe some information control. We just need to understand where and why that happens, and—hopefully—how we can mitigate it. |
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How Continuous Testing Is Done in DevOps DevOps does speed up your processes and make them more efficient, but companies must focus on quality as well as speed. QA should not live outside the DevOps environment; it should be a fundamental part. If your DevOps ambitions have started with only the development and operations teams, it’s not too late to loop in testing. You must integrate QA into the lifecycle in order to truly achieve DevOps benefits. |
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Blending Machine Learning and Hands-on Testing As your QA team grows, manual testing can lose the ability to focus on likely problem areas and instead turn into an inefficient checkbox process. Using machine learning can bring back the insights of a small team of experienced testers. By defining certain scenarios, machine learning can determine the probability that a change has a serious defect, so you can evaluate risk and know where to focus your efforts. |
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5 Key Elements for Designing a Successful Dashboard When you’re designing a dashboard to track and display metrics, it is important to consider the needs and expectations of the users of the dashboard and the information that is available. There are several aspects to consider when creating a new dashboard in order to make it a useful tool. For a mnemonic device to help you easily remember the qualities that make a good dashboard, just remember the acronym “VITAL.” |
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Risk Coverage: A New Currency for Testing In the era of agile and DevOps, release decisions need to be made rapidly—preferably, even automatically and instantaneously. Test results that focus solely on the number of test cases leave you with a huge blind spot. If you want fast, accurate assessments of the risks associated with promoting the latest release candidate to production, you need a new currency in testing: Risk coverage needs to replace test coverage. |
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Transforming a Test Automation Maintenance Nightmare into Success Best practices for test automation emphasize reliability, portability, reusability, readability, maintainability, and more. But how can your existing automated test suite adopt these qualities? Should you address these issues with your current tests, or create an entirely new set of tests? Here are some questions that will help you determine if your test automation maintenance program is operating as it should be. |
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7 Agile Testing Trends to Watch for in 2020 With 2020 upon us, software development firms seeking to increase their agility are focusing more and more on aligning their testing approach with agile principles. Let’s look at seven of the key agile testing trends that will impact organizations most this year. |
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Zero to SME: Quickly Becoming Your Own Subject Matter Expert On a new project, we often lack the luxury of having a subject matter expert available to answer our questions. When that’s the case, we have to become our own SME. Here are a few key methods from the writings and presentations of experts in various fields that deal with information gathering and rapid learning. You can easily use these methods, right now, to quickly gain the knowledge you need in order to move forward. |
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Top 10 StickyMinds Articles of 2019 Teams everywhere are looking to speed up testing without sacrificing quality, so once again, some of the top articles last year were about continuous integration, machine learning, and—of course—how to best implement and use test automation. But readers were also interested in what they shouldn't be doing, with two high-ranking articles about test practices we should stop and a tool you may be misusing. |
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Applying Data Analytics to Test Automation Testers gather lots of metrics about defect count, test case execution classification, and test velocity—but this information doesn't necessarily answer questions around product quality or how much money test efforts have saved. Testers can better deliver business value by combining test automation with regression analysis, and using visual analytics tools to process the data and see what patterns emerge. |
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