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Leave No Tester Behind Creating comprehensive automated tests within a sprint can be a challenge. If the testers don't finish the automation and the rest of the team moves on, testers get left behind and can't catch up. You need some techniques to keep everyone together and ensure that all essential work is accomplished—including test automation. |
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Comparing 4 Top Cross-Browser Testing Frameworks The market is flooded with cross-browser testing frameworks, with more options than ever before. How should you decide which option is best to test your application for compatibility with different web browsers? Let’s take a look at four of the top open source solutions today and compare their benefits and drawbacks. |
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Lessons the Software Community Must Take from the Pandemic Due to COVID-19, organizations of all types have had to implement continuity plans within an unreasonably short amount of time. These live experiments in agility have shaken up our industry, but it's also taught us a lot of invaluable lessons about digital transformation, cybersecurity, performance engineering, and more. |
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The Evolution of Modern Testing: A Slack Takeover with Adam Sandman Thought leaders from the software community are taking over the TechWell Hub to answer questions and engage in conversations. Adam Sandman, director of technology at Inflectra, hosted this Slack takeover and discussed the main challenges testers face today, what modern users expect, and how to approach test automation. |
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An Agile Mindset Teaches the Lessons We Need for COVID-19 Since we can't control the COVID-19 situation besides following safety protocols, and updates change almost daily, our circumstances necessitate agility from everyone, from employees to company leads. Let’s look at the practical agility lessons COVID-19 is teaching us and why an agile mindset is even more important now. |
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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. |
