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James Farrier

James Farrier
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Member for

6 years 7 months

I have worked in Test Automation for the last 12 years, I left to build a company to solve the challenges faced by testers, how to get reliable test results in the shortest period of time.

I founded Appsurify two years ago. Appsurify makes your software testing smarter, faster, and cheaper, allowing you to deliver new releases faster with fewer defects.

Appsurify's TestBrain makes your automated and manual testing more efficient by: (1) finding and running the small subset of tests from the full test suite needed to check each code change and get test results to developers immediately without having to wait for a full test cycle; (2) identifying and quarantining flaky test failures to prevent the builds from breaking; and (3) identifying the risks in recent commits to enable manual testers to focus their efforts where the bugs are likely hiding.

Software giants like Google, Microsoft, and Facebook are already using similar techniques to make their own testing efficient. Appsurify brings these best practices to everyone else, already integrated with common development tools.

Job Function
Project Management
Country
United States
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James Farrier

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Woman wearing a hard hat and working with a machine Blending Machine Learning and Hands-on TestingAs 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.
Brain made of computer circuits and binary code A Simpler Way of Using Machine Learning to Shift Testing LeftThe advantages of shifting left and testing as early as possible are obvious. But as you automate more testing, the test suite grows larger and larger, and it takes longer and longer to run. Instead, just automate the process of finding the right set of tests to run. The key to that is machine learning. This isn't AI bots finding bugs autonomously without creating tests; this is a different way to use machine learning, and it’s far simpler.