RAILS-DK: Dynamic Knowledge Management for Retrieval-Augmented Code Repair in Scientific Computing
Retrieval-augmented techniques improve automated code repair by grounding generation in external programming knowledge, but most prior approaches assume a static knowledge base. This assumption is problematic in scientific computing, where libraries, APIs, and dependencies evolve continuously. This paper presents RAILS...