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FDA Explores Review Framework for AI-Based Medical Devices As more medical devices are developed that employ artificial intelligence and machine learning software that can learn from real-world feedback and adaptation, the FDA announced it is taking steps to explore a new medical device regulatory framework. The goal is creating safe, beneficial, innovative medical products. |
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Using AI to Protect the Earth’s Species In addition to the many ways artificial intelligence and machine learning technologies are changing our everyday life, can they also help save our world? To safeguard the lives of millions of species in our world today, the campaign for Earth Day 2019 is “Protect Our Species,” and AI is already having an impact. |
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The AI Testing Singularity Machine learning is rapidly growing more powerful, already sometimes imitating the actions and judgments of humans better than humans. In the near future, even before machines are conscious, they will be able to mimic human software testers. What will be the impact of AI on testing? Jason Arbon has a bunch of ideas. |
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Continuous Security in Agile Development "Continuous" gets mentioned a lot in agile and DevOps, but one area that often doesn’t get enough attention is how to continuously build, test, and deliver secure applications. Just like for quality, you can’t test security in, so you need to have a plan for how to build it in. Here are some tips on how to do that. |
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Robotic Process Automation in Software Testing Robotic process automation (RPA) systems develop a list of actions to automate a task by watching a user perform that task in the application's GUI, and then repeating those tasks directly in the GUI. But RPA tools differ from other tools because they can handle data among multiple applications—including for testing. |
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The Developer’s Role in Testing and Quality Of course a developer's primary job is to produce good code, but there's also a lot they can do to contribute to quality and test their code before it gets to a tester. Code quality techniques help developers write better code, more thoroughly understand their changes, and avoid builds with many easy-to-find problems. |
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Integrating Threat Modeling into Agile Development Threat modeling helps you determine where to focus your security testing efforts when building your app. But people often wonder how it can fit into their existing agile software development process. Here are three things you can do to integrate threat modeling into your agile workflow, either early on or mid-project. |
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Merging New Codeless Test Automation with Your Existing Code-Based Test Scripts Adopting a codeless solution can be an amazing boost to quality, productivity, and tester career growth, but in most organizations, such test suites will have to be merged into existing code-based test scripts. To succeed, developers, testers, and management all should consider the differences between the two options. |
