June 11, 2024, 12:30 p.m. | Eran Stiller

InfoQ - AI, ML & Data Engineering www.infoq.com

Slack's engineering team recently published how it used a large language model (LLM) to automatically convert 15,000 unit and integration tests from Enzyme to React Testing Library (RTL). By combining Abstract Syntax Tree (AST) transformations and AI-powered automation, Slack's innovative approach resulted in an 80% conversion success rate, significantly reducing the manual effort required.

By Eran Stiller

abstract ai ai-powered architecture & design automation development engineering integration integration testing language language model language models large language large language model large language models library llm ml & data engineering react slack syntax team test automation testing tests tree unit-testing

Senior Data Engineer

@ Displate | Warsaw

Sr. Specialist, Research Automation Systems Integrator (Hybrid)

@ MSD | USA - Pennsylvania - West Point

Lead Developer-Process Automation -Python Developer

@ Diageo | Bengaluru Karle Town SEZ

RPA Engineer- Power Automate Desktop, UI Path

@ Baker Hughes | IN-KA-BANGALORE-NEON BUILDING WEST TOWER

Research Fellow (Computer Science (and Engineering)/Electronic Engineering/Applied Mathematics/Perception Sciences)

@ Nanyang Technological University | NTU Main Campus, Singapore

Analista de Ciências de dados II

@ Ingram Micro | BR Link - São Paulo