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5 Pitfalls to Avoid When Developing AI Tools Developing a tool that runs on artificial intelligence is mostly about training a machine with data. But you can’t just feed it information and expect AI to wave a magic wand and produce results. The type of data sets you use and how you use them to train the tool are important. Here are five pitfalls to be wary of. |
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Code Integration: When Moving Slowly Actually Has More Risk Many decisions about code branching models are made in the name of managing risk, and teams sometimes pick models that make integration harder in the name of safety. Moving slowly and placing barriers to change can seem safer, but agile teams work best when they acknowledge that there is also risk in deferring change. |
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Choosing the Right Threat Modeling Methodology Threat modeling has transitioned from a theoretical concept into an IT security best practice. Choosing the right methodology is a combination of finding what works for your SDLC maturity and ensuring it results in the desired outputs. Let’s look at four different methodologies and assess their strengths and weaknesses. |
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3 Software Testing Lessons from an Unlikely Source With people trying to stay isolated as much as possible due to COVID-19, going to the grocery store suddenly became something to strategize. At least making a plan, prioritizing risk, and being agile are business as usual for software testers. Here are some of the top lessons testers can learn from our current situation. |
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Fearless Refactoring, Not Reckless Refactoring Fearless refactoring is the agile concept that a developer should be able to incrementally change code without worrying about breaking it. But it's not believing that you don't need a safety net to detect and correct defects quickly when changes are made—that's just reckless. Here's how to avoid reckless refactoring. |
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Defensive Design Strategies to Prevent Flaky Tests Flaky tests could be the result of issues in the code, but more often they are due to assumptions in the test code that lead to non-relatable results. There are many reasons that tests can fail intermittently, and some can be easily avoided by applying good defensive design strategies. It's all about making your code agile. |
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Comparing XML and JSON: What’s the Difference? XML (Extensible Markup Language) and JSON (JavaScript Object Notation) are the two most common formats for data interchange. Although either can be used to receive data from a web server, there are differences that set them apart. Here are the abilities and support for each option so you can choose what works for you. |
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Shifting Security Left in Your Continuous Testing Pipeline Security is often the black sheep of testing—an afterthought that gets only a scan before release. We have to make security a first-class testing citizen with full-lifecycle support. For the best impact, introduce security testing into the early phases of the continuous testing pipeline. Here are some tools to help. |
