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layout: post | ||
title: "Automated code remediation with OpenRewrite" | ||
excerpt: "" | ||
meetup: 303194650 | ||
modified: | ||
categories: meetup | ||
hidden: false | ||
author: justine_gehring | ||
tags: [] | ||
comments: true | ||
share: true | ||
image: | ||
feature: | ||
date: 2024-09-26T17:30:00-04:00 | ||
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__Rémédiation automatique du code avec OpenRewrite__ | ||
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Justine discutera de la rémédiation automatique du code avec le moteur de refactorisation déterministe OpenRewrite, une technologie née chez Netflix en 2016. Il est conçu pour manipuler la représentation de l'arbre sémantique sans perte (LST) du code à l'aide de recettes (programmes) qui aboutissent à des transformations de code précises, tout en préservant le style à 100 %. Vous verrez comment associer la précision d'un système basé sur des règles à la puissance généraliste de l'IA. Divers cas d'utilisation seront présentés, tels que l'obtention d'une vue d'ensemble sémantique de votre code, la recommandation de modernisations adaptées à votre base de code, et la manière dont les LSTs fonctionnent comme guide et garde-fou pour les modèles. | ||
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__Justine Gehring__ | ||
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Justine Gehring est chercheuse dans le domaine du Machine Learning (ML) pour le code et des Graph Neural Networks (GNNs). Elle se concentre sur la génération de code dans des circonstances difficiles, notamment dans des scénarios tels que les données peu nombreuses où un code spécifique à une bibliothèque est requis, ainsi que la gestion d'une quantité importante de code simultanément. Justine est ingénieure de recherche chez Moderne, où elle étudie comment utiliser ML4Code à grande échelle. | ||
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Licenses Intellij à gagner ! | ||
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📍 L'évènement se déroulera dans les locaux de Expretio - 4446 St Laurent Blvd, Suite 700, Montreal, Quebec H2W 1Z5 | ||
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__Automated code remediation with OpenRewrite__ | ||
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Justine will discuss automated code remediation with the deterministic OpenRewrite refactoring engine, a technology born at Netflix in 2016. It’s built on manipulating the Lossless Semantic Tree (LST) representation of code with recipes (programs) that result in 100% accurate style-preserving code transformations. You will be shown how to couple the precision of a rules-based system with the generalist power of AI. Various use cases will be presented such as getting a semantic-based bird's eye view of your code, getting codebase-tailored recommendations for modernization, and how LSTs function as a guide and guardrails for models. | ||
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__Justine Gehring__ | ||
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Justine Gehring is a researcher in the field of Machine Learning (ML) for code and Graph Neural Networks (GNNs). Her focus lies in generating code under challenging circumstances, specifically in scenarios such as sparse data where library-specific code is required, as well as managing a substantial amount of code at a time. Justine is a research engineer at Moderne, where she studies how to use ML4Code at scale. | ||
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Intellij licenses to win! | ||
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📍 The event will take place at Expretio - 4446 St Laurent Blvd, Suite 700, Montreal, Quebec H2W 1Z5 |
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