Laminar: A New Serverless Stream-based Framework with Semantic Code
  Search and Code Completion
Zaynab Zahra Zihao Li Rosa Filgueira
This paper introduces Laminar, a novel serverless framework based on
dispel4py, a parallel stream-based dataflow library. Laminar efficiently
manages streaming workflows and components through a dedicated registry,
offering a seamless serverless experience. Leveraging large lenguage models,
Laminar enhances the framework with semantic code search, code summarization,
and code completion. This contribution enhances serverless computing by
simplifying the execution of streaming computations, managing data streams more
efficiently, and offering a valuable tool for both researchers and
practitioners.