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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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Bringing Continuous Testing to Your Organization Continuous testing means all your tests are executing all the time, providing continuous feedback into the quality and health of your applications. In order to achieve continuous testing, you must first adopt the right test automation strategy. Understanding how to bring in all different types of test automation practices as efficiently as possible enables you to get started down the path of continuous testing.
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6 Steps for Succeeding with Test Automation in Agile Lots of test automation efforts in agile software development fail, or at least do not maximize their potential. This article looks at two main reasons test automation may not live up to the expectations that testers and other stakeholders in the agile development process have, then outlines six steps to avoid falling into these traps. Here's how to succeed with test automation in an agile environment.
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Continuous Delivery Is Not a Pipeline Pretty much everything you hear about DevOps mentions “the pipeline.” Continuous delivery is not really about the pipeline, however. Continuous delivery is about two things: testing strategy and branching strategy. The pipeline is important; it is an integral part of DevOps. However, the central element is the practice of testing continually using automated tests.
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5 Key Factors to Achieve Agile Testing in DevOps Part of the path to DevOps requires adoption of agile methodologies. What does it mean for testing when you switch from the traditional waterfall model, with a few long release cycles per year, to the agile model, with changes occurring every two weeks? Here are five key factors to achieve the agile software testing necessary in DevOps.
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The Value of Test-Driven Development when Writing Changeable Code Writing changeable code makes it easier and more cost-effective to add features to existing software. Writing changeable code doesn’t take longer, but it does require paying attention to certain things when building a system. It's important to have a good suite of unit tests that support refactoring code when needed, and test-driven development helps you create independently testable code.
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Has Continuous Deployment Become a New Worst Practice? Software development has been moving toward progressively smaller and faster development cycles, and continuous integration and continuous deployment are compressing delivery times even further. But is this actually good for businesses or their users? Just because you can deploy to production quickly and frequently, should you?
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Fixing a Broken Deployment Process When you have hundreds of applications performing various functions across several environments, it's tough to push all the code when it needs to be. Here are some steps to help your own team develop the internal tooling it requires to deploy thousands of applications if needed, all in a reliable, efficient manner.
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6 Steps to a Successful DevOps Adoption Implementing DevOps practices can significantly accelerate software releases while still assuring applications meet quality objectives. But DevOps can’t be bought, bolted on, or just declared. If you’re considering a move to a DevOps delivery model, here are six approaches for ensuring a successful DevOps adoption within an organization.
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Get Smart about Your Regression Tests’ Value If you aren’t measuring the coverage your regression tests provide, you may be spending too much time for little benefit. Consider the value of your regression tests as you create and manage them. You need to be smart about the regression tests you maintain in order to gain the maximum value from the work put into creating, running, and analyzing their results.
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