Though test automation has made testing faster, quality teams struggle to prioritize end-to-end testing to maximize test coverage. It’s challenging to define the E2E scenarios similarly to unit test coverage, particularly when teams only have a small set of test needs outlined. The issue becomes even more complex when new application features are added since there’s no way to determine where more E2E tests are necessary. This talk explains how a ML engineer built and tested a new feature and how prioritization of E2E testing in Agile environments can be automated. Lauren’s team developed...
Lauren Clayberg
Software Engineer
mabl
Lauren Clayberg is a Software Engineer specializing in machine learning at mabl, where she leads development on new features such as test ID case tracking and the new url clustering feature. She has a Masters in Electrical Engineering and Computer Science with a concentration in machine learning from MIT, where she also earned her Bachelor of Science in Computer Science and Engineering. She’s very passionate about solving real problems and helping the Agile community. Her favorite projects are those where she can combine creativity with her love for computer science. Her work is driven by teamwork and she loves building tools that make collaboration easier for all Agile teams.