The goal is to create a programming language and runtime that has effectively constant-time performance for all operations, constant memory overhead, and bounded garbage collection pauses.
The authors explore the integration of metaprogramming in a call-by-value linear lambda-calculus and sketch its extension to a session type system, allowing for the setup of code-producing servers that run in parallel with the rest of the program and provide code on demand, exchanged on typed channels.
This paper presents three algorithms for checking subtyping of binary session types, along with their complexity analyses. The first algorithm is based on an inductive tree search, the second is an optimized version of the first, and the third is a new quadratic algorithm based on graph search using the concept of X Y Z W-simulation.
Gradual sensitivity typing allows programmers to smoothly evolve typed programs without any static sensitivity information towards hardened programs with a mix of static and dynamic sensitivity checking.
Learning transfers well across several programming languages.
Using Large Language Models (LLMs) to compile Arabic text code into Python code bridges linguistic barriers, revolutionizing programming for Arabic-speaking individuals.
The author explores the unification of operational logical relations through fibrations, providing a common framework for various languages and introducing differential logical relations. This approach aims to establish a solid mathematical foundation for understanding program behaviors.