Roberto Perez Alcolea
Senior Software Engineer
Netflix
If you’re interested in faster tests, flaky test detection/remediation, remote test execution, and predictive test selection, this talk is for you. Pro Tip: How they rolled out Develocity’s Predictive Test Selection AI/ML technology to save 107 days of test execution time in the first month is quite interesting.
About the session
If you’re interested in faster tests, flaky test detection/remediation, remote test execution, and predictive test selection, this talk is for you. Pro Tip: How they rolled out Develocity’s Predictive Test Selection AI/ML technology to save 107 days of test execution time in the first month is quite interesting.
Watch the video
It is well known that organizations connect software testing with software quality: making sure that the code does what it supposed to do.
Unfortunately, many organizations believe that testing is a slow process that causes stagnancy in the project. Organizations say that due to slow testing process they are not able to meet set milestones, but it doesn’t have to be this way.
The testing stage is also part of the developer experience, and making it such that engineers are productive and continue delivering software not only fast but with confidence is crucial.
In this talk, we will explore a few approaches that we are taking in order to deliver a more consistent and delightful testing experience for JVM engineers at Netflix. The end goal: speed up engineers’ feedback loop by running tests locally constantly as much as possible.
Roberto is an experienced software engineer with a focus in jvm ecosystem, developer productivity and continuous delivery. He has several years of experience using technologies for the JVM.
He’s an active maintainer of Netflix Nebula Plugins (https://nebula-plugins.github.io/) and occasional contributor to the Gradle Build tool (https://gradle.org/)
He currently works at Netflix in the JVM ecosystem team. The JVM Ecosystem Team provides the user experience for dependency management, building, packaging, and publishing JVM-based libraries and applications through providing tools, automation, and guidance to thousands of engineers at Netflix.