Home Knowledge Base Empirical Evaluation of Large Language Models for Migration of Code Fragments

Empirical Evaluation of Large Language Models for Migration of Code Fragments

No mentions found

This entity hasn't been tracked yet, or Iris is still building its knowledge base.

Related Articles from SNS

Empirical Evaluation of Large Language Models for Migration of Code Fragments to Post-Quantum Cryptography

arXiv:2606.07341v1 Announce Type: new Abstract: The transition to post-quantum cryptography (PQC) requires not only replacing vulnerable cryptographic primitives, but also refactoring the surrounding software logic. While existing PQC migration frameworks provide organizational guidance, practical code-level remediation remains largely manual and error-prone. This paper evaluates whether large language models (LLMs) can be trained to assist in the migration of pre-quantum cryptographic code...

arXiv CS 2d ago

Deep learning four decades of human migration

Abstract Human migration is a fundamental driver of global demographic change, shaping population structure, labour markets and social policy across countries1,2,3. Although long-term migration patterns are often linked to economic development4, they can shift rapidly in response to shocks such as conflict, environmental crises and political change5. Despite its importance, migration remains difficult to measure consistently: existing data are sparse, concentrated in high-income settings and...

Nature 21h ago